{"@context":"https://schema.org","@type":"ItemList","name":"Senior Machine Learning Engineer Jobs | Find ML Engineer Positions","description":"Explore the latest senior machine learning engineer job opportunities. Apply for ML engineer positions today and kickstart your career in data science.","itemListElement":[{"@type":"ListItem","position":1,"item":{"@type":"JobPosting","title":"Senior Machine Learning Engineer, Motion Planning","datePosted":"2025-08-03","description":"Woven by Toyota is enabling Toyota’s once-in-a-century transformation into a mobility company. Inspired by a legacy of innovating for the benefit of others, our mission is to challenge the current state of mobility through human-centric innovation — expanding what “mobility” means and how it serves society.
Our work centers on four pillars: AD/ADAS, our autonomous driving and advanced driver assist technologies; Arene, our software development platform for software-defined vehicles; Woven City, a test course for mobility; and Cloud & AI, the digital infrastructure powering our collaborative foundation. Business-critical functions empower these teams to execute, and together, we’re working toward one bold goal: a world with zero accidents and enhanced well-being for all.
TEAMAt Woven by Toyota, we work on a diverse set of problems ranging from solving Trajectory Planning and Decision Making problems, to optimizing latency on hardware accelerators, designing novel neural network architectures and applying and advancing the state-of-the-art of machine learning (ML) for perception, prediction, and motion planning. We are looking for doers and creative problem solvers to join us in improving mobility for everyone with self-driving technology. You will be interacting on a daily basis with other software and hardware engineers and researchers to tackle some of the most challenging problems in AI and Robotics.
WHO WE ARE LOOKING FORThe team is looking for an experienced Machine Learning Engineer to join us in developing a state-of-the-art motion planning system for autonomous driving. As an expert in machine learning in the Motion Planning team, you will be responsible to design and develop new Machine Learning models for our Motion Planners, and to deploy the model on our next-generation autonomous vehicle platform and ultimately to millions of Toyota production vehicles. The ideal candidate will have published some deep learning research in top-tier conferences such as NeurIPs or CVPR, built and deployed real-world deep learning products, and worked in a fast-paced environment along with other highly talented engineers. We recognize the unique capabilities each team member brings, and encourage applicants to reach out even if they do not match all of the characteristics described below.\n

RESPONSIBILITIES:

Motion Planning ML model R&D by prototyping, validating and iterating on existing and new model architectures leveraging imitation learning, deep reinforcement learning, and large-scale data.
Own development of new ML models end-to-end from data strategy, initial development, optimization, production platform validation, and fine tuning based on metrics and on road performance.
Lead large, multi-person projects and significantly influence the overall Motion Planning architecture and technical direction.
Enable and help other engineers on the team to be more effective through coaching and leading by example when it comes to writing high-quality code, providing high-quality code and design document reviews and delivering rigorous reports from ML experiments.
Work in a high-velocity environment and employ agile development practices.
Team player and \"get things done\" mentality
Collaborate closely with teams such as Perception, Simulation, Infrastructure, Tooling to drive unified solutions.
Closely collaborate with Motion Planning subteams to develop end-to-end solutions.

EXPERIENCE:

MS, or higher degree, in Machine Learning, Robotics, Computer Science, Computer Engineering (or other related fields)
5+ years of experience with ML frameworks such as PyTorch, Caffe, Tensorflow
Extensive experience with learning-based planning approaches like imitation learning, reinforcement learning and state-of-the-art techniques for sequential modeling like Transformer architectures, and camera input or vector/point-based representations.
Strong programming skills in Python or C++
5+ years of experience in machine learning workflows: data sampling and curation, pre-processing, model training, ablation studies, evaluation, deployment, inference optimization.
Passionate about self driving car technology and its potential for humanity.
Strong communication skills and ability to communicate concepts clearly and precisely

Nice to Have

Experience with robot motion planning techniques like trajectory optimization, sampling-based planning, model predictive control, etc or self-driving problems (Perception, Prediction, Mapping, Localization, Planning, Simulation)
Experience in writing production level code in a real-time operating system.
Experience with temporal/sequential modeling and/or reinforcement learning.
Experience in optimizing runtime-critical systems for Linux, UNIX-like real-time operating systems on automotive-grade compute platforms, and building safety-critical software architecture.

For positions based in Palo Alto, CA, the base pay for this position ranges from $140,000 - $230,000 a year
Your base salary is one part of your total compensation. We offer a base salary, short term and long term incentives, and a comprehensive benefits package. The total compensation offered to an employee will be dependent upon the individual's skills, experience, qualifications, location, and level.
WHAT WE OFFERWe are committed to creating a modern work environment that supports our employees and their loved ones. We offer many options of the best programs to allow you to do your most meaningful work and to help you shape the future of mobility.・Excellent health, wellness, dental and vision coverage・A rewarding 401k program・Flexible vacation policy・Family planning and care benefits

Our Commitment・We are an equal opportunity employer and value diversity.・Any information we receive from you will be used only in the hiring and onboarding process. Please see our privacy notice for more details.","hiringOrganization":{"@type":"Organization","name":"Woven by Toyota","sameAs":"https://woven.toyota/"},"jobLocation":{"@type":"Place","address":{"@type":"PostalAddress","addressLocality":"Palo Alto, CA","addressCountry":"United States","addressRegion":"North America"}}}},{"@type":"ListItem","position":2,"item":{"@type":"JobPosting","title":"Senior Machine Learning Engineer","datePosted":"2025-07-21","description":"

About AirGarage

AirGarage is on a mission to bring real estate online, starting with parking.

We replace broken parking machines, fragmented software, and manual, labor-intensive operations with a unified, data-rich operating system for parking real estate. We handle everything it takes to run and optimize a parking asset: payments, dynamic pricing, enforcement, license plate recognition, analytics, and more.

By building all of our technology in-house, we are able to deliver a magical experience for drivers while providing real-time visibility and revenue increases of 20-50% or more for real estate owners. That’s why national real‑estate leaders like Hines and Greystar, as well as technology companies like Meta, partner with AirGarage to optimize their parking facilities.

AirGarage uses datapoints like real-time occupancy, local events, weather, driver behavior, competitor pricing, and more to bring true intelligence to real estate owners’ assets for the first time.

We’re investing aggressively to make the physical world legible to a digital system: cameras, sensors, and software that generate a firehose of real-time data about the world around us. That data fuels models and algorithms that allow us to optimize performance at each property while giving owners the clarity and control they’ve never had before.

Before you can optimize an asset, you need to observe it. Before you can observe it, you need to bring it online.

We are starting with the $131 billion US parking real estate market because it is one of the most offline and mismanaged commercial real estate asset types. 26% of the land area in the median American urban core is dedicated to parking.

We are backed by top tier investors including Headline Growth, Andreessen Horowitz, Floodgate, Founders Fund, Abstract Ventures, and angel investors who have founded or worked at companies like Uber, Opendoor, Flexport, and more.

Want to learn more about AirGarage and the problem we're tackling?

Check out these podcasts:
https://www.youtube.com/watch?v=AU0NkDK51E4
https://youtu.be/_8aM6NQHYiE?si=p5WIujBWUA1sG-b7

THE ROLE 👨‍💻

We’re looking for a Senior Machine Learning Engineer to lead impactful projects in machine learning and software engineering across our platform. You’ll enhance our in-house License Plate Recognition (LPR) system, introduce entirely new systems, and advance our data-driven dynamic pricing and enforcement platforms. Your role involves developing efficient, practical machine learning models optimized for both edge devices and cloud deployments, as well as identifying when traditional algorithms are more effective than ML solutions. Beyond the models and algorithms, you’ll contribute to building the supporting systems by creating scalable backend systems for data ingestion, processing, and analytics. This role requires a versatile engineer who prioritizes pragmatic, effective solutions over simple one-size-fits-all approaches.

As the first dedicated machine learning hire, this is a foundational role with the opportunity to make high-impact technical decisions and establish technical best practices. This is a high-leverage role with visibility across the business and plenty of room to grow.

WHAT YOU WILL DO 🚀

Develop, deploy, and optimize machine learning models, with applications spanning computer vision, dynamic pricing, and operational intelligence.
Design and implement scalable backend systems for ingesting, processing, and analyzing large datasets.
Collaborate closely with other engineers to build the necessary infrastructure for deploying models into production environments.
Identify pragmatic opportunities for applying ML/AI, prioritizing real-world impact over hype.
Ensure the robustness, efficiency, and maintainability of our ML models and related software systems.
Conduct thorough code reviews, mentor teammates, and raise the engineering quality bar.
Work daily with product, operations, and founders to ship high‑impact features quickly.
Drive continuous improvement in tooling, processes, and developer experience.

WHAT YOU NEED 🧠

4+ years of professional experience in applied machine learning engineering, including model training, deployment, and optimization.
Strong proficiency in Python and experience with machine learning frameworks such as PyTorch, TensorFlow, or similar.
Demonstrated expertise applying computer vision algorithms and techniques (e.g., image classification, object detection, segmentation).
Proven ability in backend software engineering, including developing scalable RESTful APIs, data processing pipelines, and managing databases.
Experience with cloud platforms and containerization.
A practical, solution-oriented mindset with excellent problem-solving abilities and clear communication skills.
A self-driven, collaborative team player comfortable working in a fast-paced, ownership-driven startup environment.

THE UPSIDE 📈

📈 Equity: Have a stake in the business that you’re helping to build and grow.
🌴 Work remotely: Live and work wherever you like! We believe in folks working where they are happiest and most productive. We currently hire teammates that are located anywhere within North America.
🏥 Health insurance: We offer health insurance and currently cover 85% of the cost of medical plans for the primary employee and 50% of the cost of plans for dependents.
💻 Home office setup: Get a laptop + additional equipment needed to set you up for success.
⛺ Time to recharge: We have an unlimited PTO policy with a minimum requirement of 10 days per year.
🤑 401k: Make financial planning right for you with a 401k retirement savings program.
✈️ Team Off-sites: ~2 times per year our team comes together for a full week in places like Tahoe, Puerto Vallarta, San Diego, and Austin.
📚 BookGarage: Our team loves to learn and grow together so join us for our optional recurring book club.
🪴Room to grow: Our team will be orders of magnitude larger within a few years, as a part of our foundational team you'll have opportunities to grow with us.
🏙️ Transform our cities: The opportunity to change the way that the world thinks about real estate use in our cities.
👐 Work with a diverse team: At AirGarage, we've always been committed to building a thriving team that represents the communities we serve. Our team is currently 40% female and 30%+ from underrepresented communities.

We understand that there's no such thing as a 'perfect' candidate. We're looking for someone passionate, with grit and determination, who is excited to face the challenges of a rapidly growing startup. AirGarage is the type of company where you can grow exponentially, and we encourage you to apply to us even if you don't 100% match the candidate description.

AirGarage is an Equal Opportunity Employer. We celebrate diversity and are committed to creating an inclusive environment for all employees. Candidates and employees are always evaluated based on merit, qualifications, and performance. We will never discriminate on the basis of race, color, gender, national origin, ethnicity, veteran status, disability status, age, sexual orientation, gender identity, martial status, mental or physical disability, or any other legally protected status.

","hiringOrganization":{"@type":"Organization","name":"AirGarage","sameAs":"https://www.airgarage.com/"},"jobLocation":{"@type":"Place","address":{"@type":"PostalAddress","addressLocality":"San Francisco or Remote (United States)","addressCountry":"United States","addressRegion":"North America"}}}},{"@type":"ListItem","position":3,"item":{"@type":"JobPosting","title":"Senior Machine Learning Engineer","datePosted":"2025-07-21","description":"We are a production team dedicated to supporting and enhancing production modeling systems. Our focus is on building the most accurate models with the state-of-the-art modeling technology. We build core infrastructure and pipeline capabilities that ensure seamless data flow into our models. We also support the scaling and development of model prototypes in production environments. Our goal is to create the top-notch Machine Learning products in the real estate industry. We are seeking a Senior Machine Learning Engineer to lead the design, development, and implementation of our machine learning products.\n

What You Will Work On

Lead the development of modeling complex, real-world problems.
Lead the development of complex data pipelines to support production systems.
Lead the development efforts to bring machine learning algorithms into production.
Monitor and maintain production machine learning data pipelines.

Who We Are Looking For

Minimum 5 years experience in machine learning model development, building data pipelines and robust machine learning software systems.
Strong and in-depth knowledge of various modeling techniques and machine learning frameworks.
Strong knowledge and understanding of machine learning pipelines from standardization, normalization, clustering, modeling, scoring, validation
Strong knowledge of relational databases.
Strong Knowledge of Python, R, and SQL.
Strong knowledge of distributed systems configuration and production maintenance.
Understanding of ETL engineering and tools so you can interface with data teams.
Understanding of data design principles across multiple different storage systems.
Working knowledge of AWS.
Parsing and manipulating a variety of different datasets and formats with glue magic
Self Starter with the ability to distill ambiguity into working results
You want autonomy and are willing to take responsibility
You iterate quickly and are a continuous learner and are comfortable in a face-paced environment
Good communicator and willing to work cross-functionally with other engineering teams across the organization
Strong problem-solving skills and the ability to work effectively in a team.

What you can Expect

Compensation: The base salary for this position ranges from $136,000 to $178,000 annually, depending on your location, experience, and qualifications. Additional compensation offerings include company profit-sharing bonus program, communication stipends, and referral bonuses.
Inclusive benefits package offering:
Comprehensive medical, dental, and company paid vision insurance, 401(k) retirement plan with employer match, voluntary life and AD&D insurance options, voluntary supplemental insurances for accident, critical illness, and legal services, paid time off (PTO) and paid holidays, employee assistance and wellness programs, company paid short term disability coverage, company contributions to health saving funds (with participation in the high deductible health plan. We offer company paid access to Galileo for virtual primary care and Rula for virtual mental health resources.
Through our Anniversary Program, we celebrate the meaningful milestones and long tenure that reflect how much we value your contributions and commitment to our team.
Career and skill development resources to help advance your career and personal growth.
A mission-driven environment where your work makes a measurable impact on the real estate industry.

What We Value

Wherever it Leads, Whatever it Takes® - No matter how remote, complex, or unexpected. Our commitment never wavers.
Hire NICE people - Skills can be taught but character shines through. We seek those who bring integrity, kindness, and grit.
Lift others up - We lead with empathy and strive to improve the lives of those around us.
Sweat the details - Excellence lives in the little things. Getting it just so is how we make a big impact.
Raise the bar - We don’t settle for industry standards, we redefine them.

About Us
Our story began in the mountain town of Truckee, California more than 20 years ago, when we pioneered simple, web-based valuation technology solutions for an industry that relied on paper. Today, we’ve grown one of the highest-coverage networks of real professionals in the county. As we continue our journey to modernize valuation we’ll hold on to our promise from day one: to go wherever it leads and do whatever it takes to serve our customer with remarkable technology and uncompromising service.
Clear Capital is an equal-opportunity employer.
To all recruitment agencies: Clear Capital does not accept agency resumes. Please do not forward resumes to our jobs alias, Clear Capital employees, or any other company location. Clear Capital is not responsible for any fees related to unsolicited resumes.
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Job Description

Here at Kraft Heinz, we grow our people to grow our business, because we believe that great people make great companies. When you join our table, you can expect access to an array of holistic wellness benefits* and perks, including medical, dental and vision coverage, 7% 401(k) matching, Business Resource Groups (BRGs) to help foster diversity, inclusion, and belonging for all employees, an industry-leading total rewards package that emphasizes a high discretionary bonus. *Benefits begin 30 days after hire for hourly employees, and immediately upon hire for salaried employees. Get a peek into life here at Kraft Heinz through our Instagram and TikTok channels!

Senior Machine Learning Engineer at a Glance….
As a Senior Machine Learning Engineer at Kraft Heinz, you will be part of the DIPP – (Decision Intelligence Products & Platforms) ML Engineering team. This person will be Operating horizontally across core functions such as Supply Chain, Manufacturing, Commercial, R&D, HR, and Marketing, this team drives value through scalable ML systems and robust MLOps practices. You will lead and develop the deployment, monitoring, and governance of machine learning models, ensuring high-performance, production-grade AI systems across the enterprise.

What’s on the menu?

MLOps & Model Lifecycle Automation

Lead MLOps practices for end-to-end model management, versioning, testing, deployment, and monitoring, ensuring traceability and reproducibility
Implement model monitoring using Aporia to track performance, bias, and drift, and automate alerts and retraining workflows
Establish robust CI/CD pipelines and governance frameworks to support scalable and secure ML deployments
Ensure models meet enterprise SLAs for reliability, security, and performance

ML Platform Engineering & Architecture

Contribute to the design and evolution of the internal ML platform with reusable components, documentation, and engineering standards
Build shared infrastructure that supports experimentation, model reproducibility, auditability, and scale across domain.

Applied Machine Learning

Develop, deploy and operationalize predictive models that improve operational efficiency, forecast demand, and manage business risks
Work closely with data scientists and SMEs to translate prototypes into production-grade ML systems

Recipe for Success – apply now if this sounds like you!

Bachelor’s or Master’s in Computer Science, Engineering, or a related field
Experience with machine learning frameworks (e.g., TensorFlow, PyTorch, Scikit-learn)
Proficiency in Python, R, or other programming languages commonly used in machine learning
3+ years of experience in ML engineering and MLOps with a focus on production-scale systems
Strong knowledge of MLOps tools (e.g., AzureML, MLflow, Kubeflow, Airflow), Model Observability (e.g. Aporia) and cloud platforms (AWS, Azure, GCP)
Deep understanding of model governance, drift detection, and Responsible AI standards
Proficiency in CI/CD for ML using Azure DevOps practices
Experience with Snowflake or similar platforms for data pipeline integration
Ability to build and maintain strong relationships with stakeholders, ensuring effective communication, collaboration, and alignment on shared goals

Our Total Rewards philosophy is to provide a meaningful and flexible spectrum of programs that equitably support our diverse workforce and their families and complement Kraft Heinz’ strategy and values.

New Hire Base Salary Range:

$100,300.00 - $125,400.00

Bonus: This position is eligible for a performance-based bonus as provided by the plan terms and governing documents.

The compensation offered will take into account internal equity and may vary depending on the candidate's geographic region, job-related knowledge, skills, and experience among other factors

Benefits: Coverage for employees (and their eligible dependents) through affordable access to healthcare, protection, and saving for the future, we offer plans tailored to meet you and your family’s needs. Coverage for benefits will be in accordance with the terms and conditions of the applicable plans and associated governing plan documents.

Wellbeing: We offer events, resources, and learning opportunities that inspire a physical, social, emotional, and financial well-being lifestyle for our employees and their families.

You’ll be able to participate in a variety of benefits and wellbeing programs that may vary by role, country, region, union status, and other employment status factors, for example:

Physical - Medical, Prescription Drug, Dental, Vision, Screenings/Assessments
Social - Paid Time Off, Company Holidays, Leave of Absence, Flexible Work Arrangements, Recognition, Training
Emotional – Employee Family Assistance Program, Wellbeing Programs, Family Support Programs
Financial -Savings/Pension, Life, Accidental Death & Dismemberment, Disability, Discounted Perks

Location(s)

Toronto - Queen's Quay - Headquarters

Kraft Heinz is an Equal Opportunity Employer – Underrepresented Ethnic Minority Groups/Women/Veterans/Individuals with Disabilities/Sexual Orientation/Gender Identity and other protected classes. In order to ensure reasonable accommodation for protected individuals, applicants that require accommodation in the job application process may contact NAZTAOps@kraftheinz.com for assistance.

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Who is Flock?

Flock Safety is an all-in-one technology solution to eliminate crime and keep communities safe. Our intelligent platform combines the power of communities at scale - including cities, businesses, schools, and law enforcement agencies - to shape a safer future together. Our full-service, maintenance-free technology solution is trusted by communities across the country to help solve and deter crime in the pursuit of safer communities for everyone.

Our holistic public safety platform is comprehensive and intelligent, providing the actionable evidence needed to solve, deter and reduce crime across neighborhoods, schools, businesses and entire cities. Without compromising transparency or privacy, we are turning unbiased data into objective answers.

Flock strives to offer a career-defining experience where you can also make an impact on your community. While safety is a serious business, we are a supportive team that is optimizing the remote experience to create strong and fulfilling relationships even when we are physically apart. Our group of hard-working employees thrive in a positive and inclusive environment, where a bias towards action is rewarded.

We have raised over $700M in venture capital from investors including Tiger Global, Andreessen Horowitz, Matrix Partners, Bedrock Capital, Meritech Capital Partners, and Initialized Capital. Now surpassing a $7.5B valuation, Flock is scaling intentionally and seeking the best and brightest to help us meet our goal of reducing crime in the United States by 25% in the next three years.

The Opportunity

Flock Safety is a leading public safety company dedicated to eliminating crime through a full-service offering of hybrid hardware and software systems. Flock’s LPR and Video products detect and track objects to provide its customers with the best information to make actionable decisions. As a Senior Machine Learning Engineer, you will play a critical role in architecting and deploying large-scale, real-time, and accurate computer vision models. You will work closely with research scientists, ML engineers, infrastructure teams, and operations to develop high-performance systems for license plate and vehicle detections.

The Skillset

5+ years of industry experience in Deep Learning and Computer Vision
Experience with Computer Vision modeling, such as Object Detection and Image Classification
Experience in metric learning, contrastive learning, and embedding-based ReID models
Experience in working with hybrid systems of deployed devices working with cloud processing
Strong experience in Python
Experience leading projects from R&D to production
Experience with SQL, Git and Bash

Feeling uneasy that you haven’t ticked every box? That’s okay; we’ve felt that way too. Studies have shown women and minorities are less likely to apply unless they meet all qualifications. We encourage you to break the status quo and apply to roles that would make you excited to come to work every day.

90 Days at Flock

We are a results-oriented culture and believe job descriptions are a thing of the past. We prescribe to 90 day plans and believe that good days, lead to good weeks, which lead to good months. This serves as a preview of the 90 day plan you will receive if you were to be hired in this role at Flock Safety.

The First 30 Days

Meet the team & cross-functional stakeholders
One major cultural component within Flock’s engineering teams is the “first day push”. The first day push focuses setup and onboarding to the things that matter to deliver value.
Understand the systems and processes in place that Engineering uses, and leverage them to produce additional value.

The First 60 Days

Gather data to support model growth and expansion
R&D a new feature for the license plate model

90 Days & Beyond

Start owning experiments
Expanding the License Plate model
Monitoring model performance in production and iterating on improvements

The Interview Process

We want our interview process to be a true reflection of our culture: transparent and collaborative. Throughout the interview process, your recruiter will guide you through the next steps and ensure you feel prepared every step of the way.

Our First Chat: During this first conversation, you’ll meet with a recruiter to chat through your background, what you could bring to Flock, what you are looking for in your next role, and who we are.
The Hiring Manager Interview: You will meet with your potential future boss to really dive into the role, the team, expectations, and what success means at Flock. This is your chance to really nerd out with someone in your field.
The Panel: Learn more about the team, responsibilities, and workflows. You should be prepared to speak about past projects, how you collaborate and communicate with others, and how you live our values. Depending on the team and role you are interviewing for, you may meet with several teammates as well as cross-functional partners.
The Executive Review: A chance to meet an executive and view Flock from a different lens. Be prepared to ask well-thought-out questions about the company, culture, and more.

Salary & Equity

In this role, you’ll receive a starting salary between $175,000 and $200,000 as well as Flock Safety Stock Options. Base salary is determined by job-related experience, education/training, as well as market indicators. Your recruiter will discuss this in-depth with you during our first chat.

The Perks

🌴Flexible PTO: We seriously mean it, plus 11 company holidays.

⚕️Fully-paid health benefits plan for employees: including Medical, Dental, and Vision and an HSA match.

👪Family Leave: All employees receive 12 weeks of 100% paid parental leave. Birthing parents are eligible for an additional 6-8 weeks of physical recovery time.

🍼Fertility & Family Benefits: We have partnered with Maven, a complete digital health benefit for starting and raising a family. Flock will provide a $50,000-lifetime maximum benefit related to eligible adoption, surrogacy, or fertility expenses.

🧠Spring Health: Spring Health offers a variety of mental health benefits, including therapy, coaching, medication management, and digital tools, all tailored to each individual's needs.

💖Caregiver Support: We have partnered with Cariloop to provide our employees with caregiver support

💸Carta Tax Advisor: Employees receive 1:1 sessions with Equity Tax Advisors who can address individual grants, model tax scenarios, and answer general questions.

💚ERGs: We want all employees to thrive and feel like they belong at Flock. We offer three ERGs today - Women of Flock, Flock Proud, and Melanin Motion. If you are interested in talking to a representative from one of these, please let your recruiter know.

💻WFH Stipend: $150 per month to cover the costs of working from home.

📚Productivity Stipend: $250 per year to use on Audible, Calm, Masterclass, Duolingo, Grammarly and so much more.

🏠Home Office Stipend: A one-time $750 to help you create your dream office.

Flock is an equal opportunity employer. We celebrate diverse backgrounds and thoughts and welcome everyone to apply for employment with us. We are committed to fostering an environment that is inclusive, transparent, and collaborative. Mutual respect is central to how Flock operates, and we believe the best solutions come from diverse perspectives, experiences, and skills. We embrace our differences and know that we are stronger working together.

If you need assistance or an accommodation due to a disability, please email us at recruiting@flocksafety.com. This information will be treated as confidential and used only to determine an appropriate accommodation for the interview process.

At Flock Safety, we compensate our employees fairly for their work. Base salary is determined by job-related experience, education/training, as well as market indicators. The range above is representative of base salary only and does not include equity, sales bonus plans (when applicable) and benefits. This range may be modified in the future. This job posting may span more than one career level.

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Company Description

About us

Publift is a dynamic Adtech company dedicated to empowering online publishers and websites to maximize their revenue from display ads. We are passionate about driving publisher growth and have an amazing team committed to this mission.

Our innovative product boasts an impressive track record, delivering a remarkable 55% increase in revenue for publishers on average. This transformative impact can be especially profound for small businesses, a fact we take pride in.

Fuelled by recent enhancements in our sales capacity and product development efforts, Publift has experienced a rapid increase in growth. Currently achieving 60% year-over-year growth.

Publift's Data Science team are looking for a Senior Machine Learning Engineer to accelerate the implementation of novel machine learning products. You will be heavily involved in architectural and product design decision making and have a real impact on our customer's businesses.

At Publift, we thrive in a lively, fast-paced environment characterized by a flat organizational structure.

Join us as we embark on this exciting journey of growth and innovation at Publift.

We embrace a hybrid way of working – mixing working from home with the energy and connection that comes from being together in the office. We champion flexibility and have many policies, procedures and leave options to support flexible work.

Whats on offer.

We’re proud to be recognised as one of Australia’s Best Workplaces™ by Great Place to Work®, a Family Friendly Workplace, a WORK180 endorsed employer for women and WGEA Employer of Choice for Gender Equality.
The support of a highly engaged, high-performing team including a leadership team that you’ll actually have face time with.
24 weeks paid parental leave for primary caregivers, four weeks paid secondary caregivers leave, six weeks paid gender affirming care leave.

Job Description

What the day to day will look like:

Designing and implementing end-to-end pipelines for model training, evaluation, and deployment.
Automating a test framework for a suite of machine learning models. This may include:
- Developing integration and regression tests for ML components and data pipelines.
- Monitoring model performance and data drift using automated validation tools.
- Building tools to simulate edge cases, production-like scenarios, and adversarial conditions.
Operationalising and benchmarking shadow deployments to validate challenger model performance. This includes defining criteria for model promotion or rollback.
Contribute to the research and development of new use cases or extend challenger models.

Qualifications

We are looking for someone who:

Has a strong foundation in statistics, proficiency in Python and common ML frameworks and experience working with cloud platforms and containerised environments.
Has an in-depth understanding of ML lifecycle, from data preprocessing to deployment and monitoring.
Strong commercial experience within a nimble team.
Can deliver new technologies that have shown significant improvements in the speed at which new models are delivered.
Can explain why a model is behaving the way it does and introduce challengers to account for these situations. Additionally, you can communicate the implications for the business/product.
Communicates complex concepts clearly to both technical and non-technical stakeholders, articulating trade-offs and decision rationale.
Has demonstrated extensive knowledge of ML system design, from feature engineering to model selection and performance optimisation.
Can deploy rigorously tested challengers and define measurements of comparison with incumbents.

Additional Information

A few other things we want to let you know about...

Publift is an equal opportunity employer who prides themselves on fostering a diverse and inclusive workplace. We encourage everyone of all ages, genders and backgrounds to apply. If you’re a candidate with a disability or you’ll need some adjustments to be at your best, let us know how we can provide you with additional support.
We believe work satisfaction comes from two things: working in an unbelievably great team and solving customer problems that matter.
We know how important keeping that balance between work/life is and have a range of flexible working options on offer, including part time. We are open to this conversation during our recruitment process if you want to know more just ask!
We are a proud Circle Back Initiative Employer which means we are committed to responding to every job applicant.
Successful candidates joining the publift are required to undergo a National Police Record check and must have full-time Australian working rights on an ongoing basis.

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Company Description

Nearmap is the Australian-founded, global tech pioneer innovating the location intelligence game. Customers rely on Nearmap for consistent, reliable, high-resolution imagery, insights, and answers to create meaningful change in the world and propel industries forward.

Harnessing its own patented camera systems, imagery capture, AI, geospatial tools, and advanced SaaS platforms, Nearmap stands as the definitive source of truth that shapes the livable world.

Job Description

We're looking for a Senior Machine Learning Engineer to join our AI Data Engine team and help build the foundation that powers all of Nearmap's AI products.

The Data Engine team produces the large-scale, high-quality labeled datasets that fuel our machine learning models. But we're not just building another data pipeline – we're creating a self-improving system that intelligently optimises both model training effectiveness and labelling resource allocation. Because we know that great AI starts with great data.

For this role we’re looking for a Senior ML Engineer to focus on backend services. You'll work alongside talented AI researchers to build robust, scalable systems that power our data operations. While ML knowledge is valuable, this role centres on software engineering rather than model training.

Key Responsibilities:

Build and optimise backend services, APIs, and databases that support our ML data workflows
Design and maintain sophisticated labelling and data systems using Python, SQL, Kubernetes, Argo, and GitLab
Partner with data scientists and ML engineers to create seamless workflows across diverse ML applications
Guide architectural decisions and ensure our systems align with best practices and organisational goals
Mentor engineers at all levels while championing collaboration and operational excellence

What We're Looking For:

5+ years building scalable, production-grade software systems (ideally in ML/MLOps environments)
Strong Python skills and deep experience with distributed systems on Linux
Proven track record with CI/CD pipelines, monitoring, and production optimisation
Excellent collaboration skills – you'll work closely with data scientists and ML engineers
Bonus points for experience with Docker, Kubernetes, Snowflake, and AWS services (S3, RDS, EKS)

Qualifications

Bachelor's or Master's degree in Computer Science, Engineering, or related technical field

Additional Information

Some of our benefits

Nearmap takes a holistic approach to our employees’ emotional, physical and financial wellness. Some of our current benefits include:

Quarterly wellbeing day off - Four additional days off annually for your 'YOU' Days
Access to LinkedIn Learning
Wellbeing and technology allowance
Annual flu vaccinations
Hybrid flexibility for this role
Nearmap subscription (of course!)
Stocked kitchen with access to all the snacks you need
In-office lunch every Tuesday and Thursday at our Sydney CBD office
Showers available for anyone cycling to work or lunchtime gym-goers!

Working at Nearmap
\nWe move fast and work smart; often wearing multiple hats. We adapted to remote working with ease and are continually looking at ways to improve. We’re proud of our inclusive, supportive culture, and maintain a safe environment where everyone feels a sense of belonging and can be themselves.
\n
\nIf you can see yourself working at Nearmap and feel you have the right level of experience, we invite you to get in touch.

Read the product documentation for Nearmap AI:

https://docs.nearmap.com/display/ND/NEARMAP+AI

For a deep dive into Nearmap AI, listen to our VP of AI & Computer Vision, Mike Bewley on the Mapscaping podcast https://mapscaping.com/blogs/the-mapscaping-podcast/collecting-and-processing-aerial-imagery-at-scale

Thanks, but we got this! Nearmap does not accept unsolicited resumes from recruitment agencies and search firms. Please do not email or send unsolicited resumes to any Nearmap employee, location or address. Nearmap is not responsible for any fees related to unsolicited resumes.

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Company Description

Continental develops pioneering technologies and services for sustainable and connected mobility of people and their goods. Founded in 1871, the technology company offers safe, efficient, intelligent and affordable solutions for vehicles, machines, traffic and transportation. In 2024, Continental generated sales of €39.7 billion and currently employs around 190,000 people in 55 countries and markets.

Job Description

Continental’s digital capabilities are growing every day. Our eCommerce, Fleet Solutions and Data Science Information Technology team creates a wide range of technology solutions for Continental’s Global Sales and Marketing teams – and we want you to join us!

Our Applied Analytics and AI team continuously works on the digitalization of our business-to-business processes and end consumer communication, using modern tech stacks with a strong focus on data science and artificial intelligence. Whether you want to optimize big production machines for an impact on sustainability or work with an international sales organization -we run a diverse range of operational data-driven products across the entire value chain of a tire.

If you’d love to join a global team that works on the latest technologies and creates value-added solutions for customers, Continental is the perfect match for you.

As Senior ML Engineer your main responsibilities will be:

Architect and design machine learning systems that provide value in close collaboration with business stakeholders from various domains;
Provide technical oversight and guidance in their implementation to a team of data scientists;
Take responsibility for maintaining these systems in production;
Take co-ownership in shaping the processes, standards and conventions of our organization to increase maintainability of solutions (e.g., via technical blueprints).

Qualifications

University degree in Computer Science, Data Science, or related studies;
Proven track record of delivering business value with data products powered by machine learning;
Hands-on mentality with very good knowledge in Python;
Solid background in software-engineering best practices (e.g., design patterns, databases, code review, versioning, etc.);
Knowledge on deployment in Cloud environments (e.g., AWS or Azure);
Excellent communication skills;
Very good self-organization and autonomous working style;
Critical thinking, problem-solving mindset and the ability to quickly deep dive into new problems;
Experience with Agile project management;
Proficient English language skills (written / spoken).

Additional Information

Integration in a dynamic international work environment and team;
A wide range of application domains for ML&AI;
A state-of-the-art tech stack;
Flexible working model (hybrid);
Agile and collaborative workstyle;
Continuous opportunities for personal development and learning.

We are committed to fostering a workplace where everyone feels safe, respected, and valued. All kind of applications are welcome.

Ready to drive with Continental? Take the first step and fill in the online application.

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GoHealth Intro: As a leading health insurance marketplace, Go Health’s mission is to improve access to healthcare in America. For customers, enrolling in a health insurance plan is confusing and difficult, and seemingly small differences between plans can lead to significant out-of-pocket costs or lack of access to critical medicines and even providers. We use our technology, data science, agents, and expertise to cut through the confusion and get customers enrolled in a plan with the right coverage and benefits.

Why Apply: GoHealth has established a culture where our employees feel empowered, engaged and inspired. We are looking for builders who will contribute to the long-term health of the company. We also understand that you may not check every box in our requirements list, most applicants don’t! In fact, frequently cited statistics show that women and underrepresented groups apply to jobs only if they meet 100% of the qualifications. GoHealth encourages you to break that statistic and to apply today!

About the role:

We’re looking for a product-minded, hands-on Senior Machine Learning Engineer who can turn AI/ML ideas into high-impact, production-ready solutions. You’ll help build and scale predictive ML and GenAI systems that power core experiences for our agents and consumers—from personalized plan recommendations to process optimization and intelligent automation.

This is an end-to-end role—part builder, part researcher, part collaborator—with opportunities to shape both the technical stack and the business outcomes.

What you’ll do:

Design, develop and deploy ML/AI systems that solve core business problems—ranging from predictive modeling (e.g., acquisition, conversion, retention) to GenAI-powered tools (e.g., embeddings, retrieval-augmented generation).
Build and scale ML systems end-to-end: from feature/data engineering to training, evaluation, deployment, and monitoring.
Productionalize models using modern software engineering practices: version control, unit testing, CI/CD, scalable APIs, logging, and alerting.
Collaborate cross-functionally with Product, Engineering, and Business teams to turn ideas into measurable value-driving ML features and services.
Establish robust evaluation and monitoring frameworks to ensure model performance, drift detection, and business impact measurement.
Contribute to the evolution of GoHealth’s AI/ML platform and best practices.
Mentor junior engineers and contribute to a culture of innovation and continuous learning.

What we’re looking for:

3+ years of hands-on experience in building and deploying predictive ML models (e.g., logistic regression, LGBM, time-series forecasting).
Strong statistical and mathematical background, including experience with A/B testing, bootstrapping, sampling, and Bayesian methods.
Experience building and shipping production ML and/or GenAI systems, with awareness of architectural and operational considerations.
Expertise in Python and proficiency in SQL.
Experience working in a cloud ecosystem like AWS (e.g., SageMaker, ECS, Lambda, S3) or Databricks.
Ability to move rapidly from prototype to production with well-documented, testable code.
Familiarity with ML observability and monitoring tools, and designing systems that track both model performance and business value.
Ability to collaborate cross-functionally and communicate complex ML/AI concepts to technical and non-technical stakeholders.

Bonus Points For:

Experience with GenAI tools and techniques, such as LLMs, prompt engineering, embeddings, or RAG workflows.
Familiarity with agentic AI workflows, real-time streaming pipelines, or feature store architectures.
Experience in healthcare, consumer, financial or investment mgmt. industries.

Location: Hybrid (Merchandise Mart, Chicago IL)

Pay Range: $130,000- $150,000

The salary range for this position reflects an expected offering for this position. An employee’s actual annual salary will be based on careful consideration of additional factors such as (but not limited to): location, relevant experience/level and skillset, education and training, internal equity as well as the scope and responsibilities of the position and market considerations.

Perks/Benefits:

Open vacation policy because work life balance is important
401k program with company match
Medical, dental, vision, and life insurance benefits
Paid maternity and paternity leave
Professional growth opportunities
Generous employee referral bonuses
Employee Resource Groups

GoHealth is an Equal Opportunity Employer

#LI-SI1

GoHealth Privacy Policy

","hiringOrganization":{"@type":"Organization","name":"GoHealth","sameAs":"https://www.gohealth.com/"},"jobLocation":{"@type":"Place","address":{"@type":"PostalAddress","addressLocality":"Illinois","addressCountry":"United States","addressRegion":"North America"}}}},{"@type":"ListItem","position":10,"item":{"@type":"JobPosting","title":"Senior Machine Learning Engineer","datePosted":"2025-08-01","description":"Here’s what you’ll be doing:
Are you ready to shape the future of InsurTech with cutting-edge machine learning and AI? At Simply Business, we're not just using data; we're continuously evolving our platform with technologies like AWS, Snowflake, and Kafka to drive real value and inform company strategy. As a leading player in the market, our mission is to remain at the forefront of data engineering, ML, and AI thinking, and we need a Senior ML Engineer who shares that ambition.\n

We're looking for someone who is:

A polyglot programmer, with expertise in Python and a genuine enthusiasm for picking up new languages like Kotlin and Rust.
An excellent communicator, capable of clearly conveying complex technical concepts to diverse audiences.
Proactive in suggesting innovative tools, architectural improvements, processes, and emerging technologies.
Collaborative and a pleasure to work with, possessing strong interpersonal skills and thriving in an open, friendly, and distributed team.
Comfortable mentoring and guiding Junior and Mid-Level Engineers, sharing your expertise and fostering growth.
A reliable \"go-to\" person for tackling and resolving complex technical challenges.

As our Senior ML Engineer, you'll:

be hands-on in developing and continuously evolving our class-leading data and ML platform infrastructure, balancing maintenance with exciting greenfield projects.
develop and maintain our real-time model serving infrastructure, utilising technologies such as Kafka, Python, Docker, Apache Flink, Airflow, and Databricks.
Actively assist in model development and debugging using tools like PyTorch, Scikit-learn, MLFlow, and Pandas, working with models from gradient boosting classifiers to custom GPT-based solutions.
gain a deep understanding of Simply Business's wider data ecosystem to build efficient and scalable machine learning systems.
work collaboratively within a friendly international team, where your ideas are valued, and you have ample opportunities to grow, explore, and contribute.
be part of an agile environment, contributing ideas and helping to prioritise technical work, with the flexibility to switch between office and remote working.

(We know it’s tough, but please try to avoid the confidence gap. You don’t have to match all the bullet points above to be considered for this role.)
We encourage people of all different backgrounds and identities to apply. We are committed to maintaining an inclusive, supportive place for you to be you and do your very best work.
If you're passionate about pushing the boundaries of machine learning, building robust, scalable systems, and working with cutting-edge technologies like custom GPT models and real-time inference, Simply Business is where you'll make a real impact.
We foster an environment where your technical interests are encouraged, and your professional development is fully supported with budgets for conferences, courses, and workshops. Come join a team that embraces new ideas and empowers you to drive the future of InsurTech! Apply Today","hiringOrganization":{"@type":"Organization","name":"Simply Business","sameAs":"https://www.simplybusiness.co.uk/"},"jobLocation":{"@type":"Place","address":{"@type":"PostalAddress","addressLocality":"London, UK","addressCountry":"United Kingdom","addressRegion":"Europe"}}}},{"@type":"ListItem","position":11,"item":{"@type":"JobPosting","title":"Senior Machine Learning Engineer","datePosted":"2025-07-16","description":"

ApplyBoard simplifies the study abroad search, application, and acceptance process by connecting international students, recruitment partners, and educational institutions on one intuitive and personalized platform. ApplyBoard is a mission-driven, hyper-growth organization. It has been attracting dedicated individuals for more than eight years who are inspired every day to break down barriers to international education and take their careers to new heights at a company that will invest in their career growth. Our six core values are our compass in our mission to Educate the World and the foundation of our unique company culture. As an organization built on a foundation of diversity, it’s important that our team members are representative of the students from more than 150 countries that we support.

The Role

As part of the ApplyBoard AI team, your mission is to help develop and productionize AI services and capabilities that help other teams to advance their services for students and recruitment partners.

You will be a senior member of a team that delivers AI capabilities to help other teams. As a Senior Machine Learning Engineer, you value collaboration and nurture innovation while working in an energetic team. Your strong foundation in productionizing machine learning models will be valuable in enabling a data-driven culture company-wide. You are expected to work on continuous improvement of our best practices for AI services and ensuring that our models are accurate, reliable, and explainable.

Responsibilities

Developing and productionizing new machine learning models
Building and documenting APIs
Improving the machine learning development & deployment pipeline
Maintaining existing machine learning models
Performing statistical analysis of model performance
ML Ops and collaboration with DevOps
Building internal demos and dashboards of our products to get feedback from different departments

Qualifications

7+ years of experience in software engineering or back-end engineering
5+ years of experience in productionizing machine learning (ML) systems
In-depth understanding of researching, designing, developing, and deploying ML systems, models, and schemes
Hands-on experience of deploying ML models/systems to AWS infrastructure
Performing statistical analysis and using results to improve models
Training and retraining ML systems and models as needed
Experience with Python, Docker containers, and AWS CDK deployment
Familiarity with ML frameworks and libraries
Experience of development and deployment with AWS Bedrock
Strong analytical and problem solving skills
Ability to communicate effectively with people who are both highly technical, and non-technical alike
Driven, passionate and creative, and thrives in a fast-paced environment

Ideally, you also have experience with many of:

AWS Machine Learning Specialty Certificate
Jenkins, CodeBuild, Terraform, Helm Charts
AWS API Gateway, CloudFront, Lambda
Data Pipeline, Kubernetes, New Relic
Microservices, Kinesis, Kafka

About ApplyBoard

ApplyBoard empowers students around the world to access the best education. With more than 1,000,000 students from over 150 countries helped with their journey in less than a decade, we are just getting started.

ApplyBoard’s 1,200 global team members in 30 countries assist students and our 1,500 partner institutions by empowering the international student sector with innovative technology and insights. As a five-time consecutive Deloitte Fast 50 and Fast 500 ranked company, ApplyBoard is growing and scaling like few other companies. On top of our strong growth, our people are growing personally and professionally. ApplyBoard India was Great Place to Work® Institute (India) certified for outstanding employee experience and workplace culture.

Thank you for your interest in joining the ApplyBoard Team and being part of our mission to Educate the World. While we are lucky to attract a high level of interest in each of our roles, only qualified applicants will be contacted and selected for an interview.

ApplyBoard welcomes and encourages applications from people with disabilities. Accommodations are available upon request for candidates in all aspects of the hiring and selection process.

","hiringOrganization":{"@type":"Organization","name":"ApplyBoard","sameAs":"https://www.applyboard.com/"},"jobLocation":{"@type":"Place","address":{"@type":"PostalAddress","addressLocality":"Kitchener, Canada","addressCountry":"Canada","addressRegion":"North America"}}}},{"@type":"ListItem","position":12,"item":{"@type":"JobPosting","title":"Senior Machine Learning Engineer","datePosted":"2025-08-04","description":"

Company Description

NIQ is the world’s leading consumer intelligence company, delivering the most complete understanding of consumer buying behavior and revealing new pathways to growth. In 2023, NIQ combined with GfK, bringing together the two industry leaders with unparalleled global reach. With a holistic retail read and the most comprehensive consumer insights—delivered with advanced analytics through state-of-the-art platforms—NIQ delivers the Full View™. NIQ, is an Advent International portfolio company with operations in 100+ markets, covering more than 90% of the world’s population. For more information, visit NIQ.com.

Job Description

NIQ is seeking a highly skilled and experienced Senior ML Engineer to join our dynamic team. As a Senior ML Engineer at NIQ, you will play a crucial role in developing and implementing advanced AI/GenAI models and algorithms to solve complex business problems. You will collaborate closely with cross-functional teams to design, build, and deploy scalable AI/GenAI solutions.

Location: Spain (remote work is allowed 4 days per week).

Responsibilities:

Develop and implement AI/GenAI models and algorithms using Python programming language, jointly with knowledge about PyTorch/Tensorflow, Pandas, sklearn and similar AI/GenAI libraries.
Utilize ML fundamentals, including deep learning, optimization techniques, NLP, and Large Language Models (LLMs), to solve real-world problems.
Work closely with data scientists and engineers to gather requirements, perform data analysis, and develop end-to-end ML pipelines.
Conduct experiments and perform model evaluation to ensure the robustness, scalability, and accuracy of AI/GenAI solutions. • Optimize and fine-tune AI/GenAI models for performance and efficiency.
Collaborate with cloud computing teams to deploy AI/GenAI models on cloud platforms, preferably Azure.
Utilize SQL for data Extraction, Transformation, and Loading (ETL) processes.
Stay updated with the latest advancements in AI/GenAI.

Qualifications

Bachelor's degree or higher in Computer Science, Engineering, Mathematics, or related field. • Proven experience 5 years working as a Senior ML Engineer or similar role.
Strong proficiency in Python programming language.
In-depth knowledge of ML fundamentals, including deep learning, optimization techniques, generative AI, NLP, and LLMs.
Experience with cloud computing platforms (knowledge of Azure is a plus).
Familiarity with SQL for data manipulation and analysis.
Excellent problem-solving skills and attention to detail.
Strong communication and collaboration skills. • Ability to thrive in a fast-paced, dynamic environment.

Additional Information

Why Join Us:

Opportunity to work on cutting-edge projects at the forefront of technology.
Collaborative and innovative work environment.
Competitive salary and benefits package.
Continuous learning and professional development opportunities

Our Benefits

Flexible working environment
Volunteer time off
LinkedIn Learning
Employee-Assistance-Program (EAP)

About NIQ

NIQ is the world’s leading consumer intelligence company, delivering the most complete understanding of consumer buying behavior and revealing new pathways to growth. In 2023, NIQ combined with GfK, bringing together the two industry leaders with unparalleled global reach. With a holistic retail read and the most comprehensive consumer insights—delivered with advanced analytics through state-of-the-art platforms—NIQ delivers the Full View™. NIQ is an Advent International portfolio company with operations in 100+ markets, covering more than 90% of the world’s population.

For more information, visit NIQ.com

Want to keep up with our latest updates?

Our commitment to Diversity, Equity, and Inclusion

NIQ is committed to reflecting the diversity of the clients, communities, and markets we measure within our own workforce. We exist to count everyone and are on a mission to systematically embed inclusion and diversity into all aspects of our workforce, measurement, and products. We enthusiastically invite candidates who share that mission to join us. We are proud to be an Equal Opportunity/Affirmative Action-Employer, making decisions without regard to race, color, religion, gender, gender identity or expression, sexual orientation, national origin, genetics, disability status, age, marital status, protected veteran status or any other protected class. Our global non-discrimination policy covers these protected classes in every market in which we do business worldwide. Learn more about how we are driving diversity and inclusion in everything we do by visiting the NIQ News Center: https://nielseniq.com/global/en/news-center/diversity-inclusion

","hiringOrganization":{"@type":"Organization","name":"NielsenIQ","sameAs":"https://nielseniq.com"},"jobLocation":{"@type":"Place","address":{"@type":"PostalAddress","addressLocality":"Madrid, M, Spain","addressCountry":"Spain","addressRegion":"Europe"}}}},{"@type":"ListItem","position":13,"item":{"@type":"JobPosting","title":"Senior Machine Learning Engineer","datePosted":"2025-08-03","description":"Introduction PhysicsX is a deep-tech company with roots in numerical physics and Formula One, dedicated to accelerating hardware innovation at the speed of software.We are building an AI-driven simulation software stack for engineering and manufacturing across advanced industries. By enabling high-fidelity, multi-physics simulation through AI inference across the entire engineering lifecycle, PhysicsX unlocks new levels of optimization and automation in design, manufacturing, and operations — empowering engineers to push the boundaries of possibility. Our customers include leading innovators in Aerospace & Defense, Materials, Energy, Semiconductors, and Automotive.
We are about to take the next leap in building out our technology platform and product offering. In this context, we are looking for a capable and enthusiastic machine learning engineer to join our team. If all of this sounds exciting to you, we would love to talk.
Note: We are currently recruiting for multiple positions, however please only apply for the role that best aligns with your skillset and career goals.\n

What you will do

Work closely with our simulation engineers, data scientists and customers to develop an understanding of the physics and engineering challenges we are solving
Design, build and test data pipelines for machine learning that are reliable, scalable and easily deployable
Explore and manipulate 3D point cloud & mesh data
Own the delivery of technical workstreams, potentially while mentoring more junior colleagues
Create analytics environments and resources in the cloud or on premise, spanning data engineering and science
Identify the best libraries, frameworks and tools for a given task, make product design decisions to set us up for success
Work at the intersection of data science and software engineering to translate the results of our R&D and projects into re-usable libraries, tooling and products
Continuously apply and improve engineering best practices and standards and coach your colleagues in their adoption

What you bring to the table

Enthusiasm about using machine learning for science and engineering
Strong problem-solving skills and the ability to analyse issues, identify causes, and recommend solutions quickly
Excellent collaboration and communication skills - with teams and customers alike
(For more experienced candidates) Passion and track record of managing, mentoring and coaching more junior colleagues
3-6 years’ experience in a data-driven role, with exposure to software engineering concepts and best practices (e.g., versioning, testing, CI/CD, API design, MLOps)
Building machine learning models and pipelines in Python, using common libraries and frameworks (e.g., TensorFlow, MLFlow)
Distributed computing frameworks (e.g., Spark, Dask)
Cloud platforms (e.g., AWS, Azure, GCP) and HP computing
Containerization and orchestration (Docker, Kubernetes)
Ability to scope and effectively deliver projects

What we offer

Equity options – share in our success and growth.
10% employer pension contribution – invest in your future.
Free office lunches – great food to fuel your workdays.
Flexible working – balance your work and life in a way that works for you.
Hybrid setup – enjoy our new Shoreditch office while keeping remote flexibility.
Enhanced parental leave – support for life’s biggest milestones.
Private healthcare – comprehensive coverage
Personal development – access learning and training to help you grow.
Work from anywhere – extend your remote setup to enjoy the sun or reconnect with loved ones.

Our stance We value diversity and are committed to equal employment opportunity regardless of sex, race, religion, ethnicity, nationality, disability, age, sexual orientation or gender identity. We strongly encourage individuals from groups traditionally underrepresented in tech to apply. To help make a change, we sponsor bright women from disadvantaged backgrounds through their university degrees in science and mathematics. ","hiringOrganization":{"@type":"Organization","name":"PhysicsX","sameAs":"https://www.physicsx.ai/"},"jobLocation":{"@type":"Place","address":{"@type":"PostalAddress","addressLocality":"Shoreditch, London","addressCountry":"United Kingdom","addressRegion":"Europe"}}}},{"@type":"ListItem","position":14,"item":{"@type":"JobPosting","title":"Senior Machine Learning Engineer","datePosted":"2025-06-30","description":"

Company Description

It all started in sunny San Diego, California in 2004 when a visionary engineer, Fred Luddy, saw the potential to transform how we work. Fast forward to today — ServiceNow stands as a global market leader, bringing innovative AI-enhanced technology to over 8,100 customers, including 85% of the Fortune 500®. Our intelligent cloud-based platform seamlessly connects people, systems, and processes to empower organizations to find smarter, faster, and better ways to work. But this is just the beginning of our journey. Join us as we pursue our purpose to make the world work better for everyone.

Job Description

Team Overview:

Join our pioneering Core-LLM platform team, dedicated to pushing the boundaries of Generative AI. We focus on developing robust, scalable, and safe machine learning models, particularly LLMs, SLMs, Large Reasoning Models (LRMs) and SRMs that power cutting-edge ServiceNow products and features. As a Senior Manager, you will lead a talented team of machine learning engineers, shaping the future of our AI capabilities and ensuring the ethical and effective deployment of our technology.

What you get to do in this role:

Generate and evaluate synthetic data tailored to improve the robustness, performance, and safety of machine learning models, particularly large language models (LLMs).
Train and fine-tune models using curated datasets, optimizing for performance, reliability, and scalability.
Design and implement evaluation metrics to rigorously measure and monitor model quality, safety, and effectiveness.
Conduct experiments to validate model behavior and improve generalization across diverse use cases.
Collaborate with engineering and research teams to identify risks and recommend AI safety mitigation strategies.
Participate in the development, deployment, and continuous improvement of end-to-end AI solutions.
Contribute to architectural and technology decisions related to AI infrastructure, frameworks, and tooling.
Promote modern engineering practices including continuous integration, continuous delivery, and containerized workflows.

Qualifications

Key qualifications:

5+ years of experience in machine learning, deep learning, and AI systems.
Proficiency in Python and frameworks like PyTorch, TensorFlow, and NumPy.
Experience in synthetic data generation, model training, and evaluation in real-world environments.
Solid understanding of LLM fine-tuning, prompting, and robustness techniques.
Knowledge of AI safety principles and experience identifying and mitigating model risks.
Hands-on experience deploying and optimizing models using platforms such as Triton Inference Server.
Familiarity with CI/CD, automated testing, and container orchestration tools like Docker and Kubernetes.
Experience with prompt engineering: ability to craft, test, and optimize prompts for task accuracy and efficiency

Additional Information

Work Personas

We approach our distributed world of work with flexibility and trust. Work personas (flexible, remote, or required in office) are categories that are assigned to ServiceNow employees depending on the nature of their work and their assigned work location. Learn more here. To determine eligibility for a work persona, ServiceNow may confirm the distance between your primary residence and the closest ServiceNow office using a third-party service.

Equal Opportunity Employer

ServiceNow is an equal opportunity employer. All qualified applicants will receive consideration for employment without regard to race, color, creed, religion, sex, sexual orientation, national origin or nationality, ancestry, age, disability, gender identity or expression, marital status, veteran status, or any other category protected by law. In addition, all qualified applicants with arrest or conviction records will be considered for employment in accordance with legal requirements.

Accommodations

We strive to create an accessible and inclusive experience for all candidates. If you require a reasonable accommodation to complete any part of the application process, or are unable to use this online application and need an alternative method to apply, please contact globaltalentss@servicenow.com for assistance.

Export Control Regulations

For positions requiring access to controlled technology subject to export control regulations, including the U.S. Export Administration Regulations (EAR), ServiceNow may be required to obtain export control approval from government authorities for certain individuals. All employment is contingent upon ServiceNow obtaining any export license or other approval that may be required by relevant export control authorities.

","hiringOrganization":{"@type":"Organization","name":"ServiceNow","sameAs":"https://www.servicenow.com"},"jobLocation":{"@type":"Place","address":{"@type":"PostalAddress","addressLocality":"Hyderabad, India","addressCountry":"India","addressRegion":"Asia/Pacific"}}}},{"@type":"ListItem","position":15,"item":{"@type":"JobPosting","title":"Senior Machine Learning Engineer","datePosted":"2025-06-30","description":"

About the team

As the engine behind Zillow Group's mission to build a seamless digital real estate marketplace, the Shopping AI team is fundamentally redefining how millions of people discover and shop for homes. Our team of engineers and scientists builds and owns the production machine learning systems that power Zillow's core user experience, including personalized ranking & recommendations, semantic search, autocomplete, and display optimization. Working closely with product and design, we apply the latest advancements in AI to solve unique, large-scale challenges. As we look forward, we are tackling the next generation of questions, including how generative AI can unlock intuitive, personalized experiences for every home shopper.

About the role

You Will Get To:

Design, build, and ship production new machine learning models that power core product features on the Zillow app, website, and email/push notifications.
Re-architect our core home ranking and recommendation systems to support advanced neural networks and dramatically accelerate the pace of experimentation across surfaces.
Own the full lifecycle of your models, from offline experimentation and prototyping with massive datasets to online deployment, A/B testing, and performance monitoring.
Pioneer the application of cutting-edge deep learning and large language models (LLMs) to improve our home shopping experience.
Develop new AI components that optimize how we display and when we recommend homes, ensuring we connect shoppers with the right content on the right properties at the right time.
Collaborate in a cross-functional group of engineers, applied scientists, product managers, and designers to define, execute, and iterate on the team's strategic roadmap.
Contribute to the team's engineering excellence by improving our machine learning infrastructure, development standards, and shared tooling.
Act as a key technical voice, mentoring other engineers and helping to shape the long-term vision for artificial intelligence in the home shopping experience.

This role has been categorized as a Remote position. “Remote” employees do not have a permanent corporate office workplace and, instead, work from a physical location of their choice, which must be identified to the Company. U.S. employees may live in any of the 50 United States, with limited exceptions.

In California, Colorado, Connecticut, Hawaii, Maryland, Massachusetts, Nevada, New Jersey, New York, Vermont, Washington state, and Washington DC the standard base pay range for this role is $168,600.00 - $269,400.00 Annually. This base pay range is specific to California, Colorado, Connecticut, Hawaii, Maryland, Massachusetts, Nevada, New Jersey, New York, Vermont, Washington state, and Washington DC and may not be applicable to other locations.

In addition to a competitive base salary this position is also eligible for equity awards based on factors such as experience, performance and location. Actual amounts will vary depending on experience, performance and location.

Who you are

Must Have:

3-5 years of experience in developing applications in search, personalized ranking, or recommender systems
Experience developing and deploying ML models that scale to high-traffic, latency sensitive customer-facing services (100s of millions of requests per day)
Strong programming skills in a high-level language such as Python or Java
Familiarity with common machine learning libraries like PyTorch, TensorFlow, Catboost, scikit-learn and huggingface (repository)
Expertise with large scale distributed data processing systems such as Hive, Spark, Airflow, or Databricks
Experience owning the full lifecycle of customer facing machine learning models, from offline experimentation and prototyping to online deployment, A/B testing, and performance monitoring
Here at Zillow - we value the experience and perspective of candidates with non-traditional backgrounds. We encourage you to apply if you have transferable skills or related experiences

Preferred:

A Master's degree + 3 yrs or BS with a minimum of 5 yrs of experience (preferably in large consumer tech companies)
Prior experience or high level of curiosity with generative AI and excitement to collaborate on what they’ve learned!

Get to know us

Zillow is reimagining real estate to make home a reality for more and more people.

As the most-visited real estate website in the United States, Zillow® and its affiliates help movers find and win their home through digital solutions, first class partners, and easier buying, selling, financing and renting experiences. Millions of people visit Zillow Group sites every month to start their home search, and now they can rely on Zillow to help make it easier to move. The work we do helps people get home and no matter what job you're in, you will play a critical role in making home a reality for more and more people.

Our efforts to streamline the real estate transaction are supported by a deep-rooted culture of innovation, our passion to redefine the employee experience, a fundamental commitment to Equity and Belonging, and world-class benefits. These benefits include comprehensive medical, dental, vision, life, and disability coverages as well as parental leave, family benefits, retirement contributions, and paid time off. We’re also setting the standard for work experiences of the future, where our employees are supported in doing their best work and living a flexible, well-balanced life. But don’t just take our word for it. Read recent reviews on Glassdoor and recent recognition from multiple organizations, including: the 100 Best Companies to Work For, Glassdoor Employees’ Choice Award, Bloomberg Gender-Equality Index, Human Rights Campaign (HRC) Corporate Equity Index, and TIME 100 Most Influential Companies list.

Zillow Group is an equal opportunity employer committed to fostering an inclusive, innovative environment with the best employees. We are committed to equal employment opportunity regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability, gender identity or Veteran status. If you have a disability or special need that requires accommodation, please contact your recruiter directly.

Qualified applicants with arrest or conviction records will be considered for employment in accordance with applicable state and local law.

Applicants who receive job offers from Zillow Group will be asked to sign a Proprietary Rights Agreement which includes confidentiality, intellectual property assignment, customer and employee non-solicitation, and non-competition provisions. If you are contacted for a role at Zillow Group and wish to review a copy of the Proprietary Rights Agreement prior to receiving an offer, you may request a copy from your Recruiter.

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We're Celonis, the global leader in Process Mining technology and one of the world's fastest-growing SaaS firms. We believe there is a massive opportunity to unlock productivity by placing data and intelligence at the core of business processes - and for that, we need you to join us.

The Team

Celonis AI Group (CeloAI) is a newly formed organization within Celonis that is dedicated to developing state-of-the-art AI/ML (and broadly intelligent) technologies for Celonis products (e.g., the Execution Management System / EMS) and empower enterprises and institutions to make intelligent business decisions and achieve operational excellence. Our dual mission focuses on both the immediate term goals of designing and implementing advanced AI/ML product features and solutions for our customers and the long term goals of establishing competitive advantages of Celonis for execution management.

We are a global organization with presence in both Germany and the US. CeloAI US has its main presence in New York, NY but also remote presences across the US.

The Role

As a software engineer (machine learning), you are responsible for designing and developing product features and customer solutions, along with the underlying infrastructure, that are based on AI/ML approaches. You may interact closely with solution engineers, customer value architects, and execution management consultants within the Go-to-Market organization and product managers and software engineers within the product and engineering organization to build scalable and high quality AI/ML features and solutions for our customers.

You may also be responsible for designing and implementing new foundational technical components that will power the next generation of EMS and elevate the impact Celonis has on our customers. These components may span the areas of computer vision, natural language processing, data mining, recommendation, knowledge base, business intelligence, and other AI technologies.

The work you’ll do

Deeply understand the business needs of Celonis customers, formulate the business needs into concrete technical problems, often AI related
Determine which AI/ML approach, if any, is suited for the problem
Design and develop scalable and high quality AI/ML models or otherwise intelligent approaches
Design and implement scalable and robust data collection mechanisms
Design and implement principled evaluation mechanisms
Design and build robust and low latency infrastructure to serve the AI/ML models and meet the demands of Celonis customers
Design and develop intelligent techniques to understand, represent, and integrate enterprise operational data (e.g., processes)
Design and build APIs and infrastructure to serve such data at scale and with low latency
Design and implement intelligent ways to ensure freshness and accuracy of such data across thousands of enterprise customers.

The qualifications you need

Bachelor’s degree, Master’s degree, or equivalent practical experience ((in Computer Science or related fields) with 3-5+ years of experience
PhD degree (in Computer Science or related fields) with 1-3+ years of experience
Strong communication and collaboration skills
Identify with the Celonis value of customer first, passionate about solving real world customer problems with a focus on finding the right solution regardless of the nature of the solution
Passionate about developing scalable and efficient AI/ML solutions
Passionate about building high quality AI/ML solutions with clear and repeatable evaluation mechanisms

The base salary range below is for the role in the specified location, based on a Full Time Schedule.

Total compensation package will include base salary + bonus/commission + equity + benefits (health, dental, life, 401k, and paid time off). Please note that the base salary range is a guideline, and that the actual total compensation offer will be determined based on various factors, including, but not limited to, applicant's qualifications, skills, experiences, and location.The base salary range below is for the role in New York, based on a Full Time Schedule. $166,000—$204,000 USD

What Celonis Can Offer You:

Pioneer Innovation: Work with the leading, award-winning process mining technology, shaping the future of business.
Accelerate Your Growth: Benefit from clear career paths, internal mobility, a dedicated learning program, and mentorship opportunities.
Receive Exceptional Benefits: Including generous PTO, hybrid working options, company equity (RSUs), comprehensive benefits, extensive parental leave, dedicated volunteer days, and much more.
Prioritize Your Well-being: Access to resources such as gym subsidies, counseling, and well-being programs.
Connect and Belong: Find community and support through dedicated inclusion and belonging programs.
Make Meaningful Impact: Be part of a company driven by strong values that guide everything we do: Live for Customer Value, The Best Team Wins, We Own It, and Earth Is Our Future.
Collaborate Globally: Join a dynamic, international team of talented individuals.
Empowered Environment: Contribute your ideas in an open culture with autonomous teams.

About Us:

Celonis makes processes work for people, companies and the planet. The Celonis Process Intelligence Platform uses industry-leading process mining and AI technology and augments it with business context to give customers a living digital twin of their business operation. It’s system-agnostic and without bias, and provides everyone with a common language for understanding and improving businesses. Celonis enables its customers to continuously realize significant value across the top, bottom, and green line. Celonis is headquartered in Munich, Germany, and New York City, USA, with more than 20 offices worldwide.

Get familiar with the Celonis Process Intelligence Platform by watching this video.

Celonis Inclusion Statement:

At Celonis, we believe our people make us who we are and that “The Best Team Wins”. We know that the best teams are made up of people who bring different perspectives to the table. And when everyone feels included, able to speak up and knows their voice is heard - that's when creativity and innovation happen.

Your Privacy:

Any information you submit to Celonis as part of your application will be processed in accordance with Celonis’ Accessibility and Candidate Notices

By submitting this application, you confirm that you agree to the storing and processing of your personal data by Celonis as described in our Privacy Notice for the Application and Hiring Process.

Please be aware of common job offer scams, impersonators and frauds. Learn more here.

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The Team

We are a global organization with presence in both Germany and the US. CeloAI US has its main presence in New York, NY but also remote presences across the US.

The Role

The work you’ll do

Deeply understand the business needs of Celonis customers, formulate the business needs into concrete technical problems, often AI related
Determine which AI/ML approach, if any, is suited for the problem
Design and develop scalable and high quality AI/ML models or otherwise intelligent approaches
Design and implement scalable and robust data collection mechanisms
Design and implement principled evaluation mechanisms
Design and build robust and low latency infrastructure to serve the AI/ML models and meet the demands of Celonis customers
Design and develop intelligent techniques to understand, represent, and integrate enterprise operational data (e.g., processes)
Design and build APIs and infrastructure to serve such data at scale and with low latency
Design and implement intelligent ways to ensure freshness and accuracy of such data across thousands of enterprise customers.

The qualifications you need

Bachelor’s degree, Master’s degree, or equivalent practical experience ((in Computer Science or related fields) with 3-5+ years of experience
PhD degree (in Computer Science or related fields) with 1-3+ years of experience
Strong communication and collaboration skills
Identify with the Celonis value of customer first, passionate about solving real world customer problems with a focus on finding the right solution regardless of the nature of the solution
Passionate about developing scalable and efficient AI/ML solutions
Passionate about building high quality AI/ML solutions with clear and repeatable evaluation mechanisms

The base salary range below is for the role in the specified location, based on a Full Time Schedule.

Total compensation package will include base salary + bonus/commission + equity + benefits (health, dental, life, 401k, and paid time off). Please note that the base salary range is a guideline, and that the actual total compensation offer will be determined based on various factors, including, but not limited to, applicant's qualifications, skills, experiences, and location.The base salary range below is for the role in California, based on a Full Time Schedule. $165,000—$214,000 USD

What Celonis Can Offer You:

Pioneer Innovation: Work with the leading, award-winning process mining technology, shaping the future of business.
Accelerate Your Growth: Benefit from clear career paths, internal mobility, a dedicated learning program, and mentorship opportunities.
Receive Exceptional Benefits: Including generous PTO, hybrid working options, company equity (RSUs), comprehensive benefits, extensive parental leave, dedicated volunteer days, and much more.
Prioritize Your Well-being: Access to resources such as gym subsidies, counseling, and well-being programs.
Connect and Belong: Find community and support through dedicated inclusion and belonging programs.
Make Meaningful Impact: Be part of a company driven by strong values that guide everything we do: Live for Customer Value, The Best Team Wins, We Own It, and Earth Is Our Future.
Collaborate Globally: Join a dynamic, international team of talented individuals.
Empowered Environment: Contribute your ideas in an open culture with autonomous teams.

About Us:

Get familiar with the Celonis Process Intelligence Platform by watching this video.

Celonis Inclusion Statement:

Your Privacy:

Any information you submit to Celonis as part of your application will be processed in accordance with Celonis’ Accessibility and Candidate Notices

By submitting this application, you confirm that you agree to the storing and processing of your personal data by Celonis as described in our Privacy Notice for the Application and Hiring Process.

Please be aware of common job offer scams, impersonators and frauds. Learn more here.

","hiringOrganization":{"@type":"Organization","name":"Celonis","sameAs":"https://www.celonis.com/"},"jobLocation":{"@type":"Place","address":{"@type":"PostalAddress","addressLocality":"Redwood City, US, California","addressCountry":"United States","addressRegion":"North America"}}}},{"@type":"ListItem","position":18,"item":{"@type":"JobPosting","title":"Senior Machine Learning Engineer","datePosted":"2025-07-22","description":"

Founded in 2012, H2O.ai is at the forefront of the AI movement to democratize Generative AI. H2O.ai’s open-source Generative AI and Enterprise h2oGPT, combined with Document AI and the award-winning autoML Driverless AI, have transformed more than 20,000 global organizations and over half of the Fortune 500 and household brands, including AT&T, Commonwealth Bank of Australia, Chipotle, ADP, Workday, Progressive Insurance, and AES.

Our “AI for Good” program supports nonprofit groups, foundations, and communities in their efforts to advance education, healthcare, and environmental conservation, including identifying areas vulnerable to natural disasters and protecting endangered species.

We have a vibrant community of two million data scientists worldwide and aim to bring together the world’s top data scientists with customers to co-create GenAI applications that are usable and valuable by everyone. Business users can now leverage the power of LLMs to enhance productivity with enterprise applications.

H2O.ai is a Visionary in the 2024 Gartner® Magic Quadrant™ for Data Science and Machine Learning Platforms. We are the only provider in the market to offer both Predictive AI and Generative AI on premise and air gapped, in addition to supporting all cloud environments

About This Opportunity

H2O.ai is at the forefront of the rapidly evolving MLOps landscape. We're leveraging MLOps to transform machine learning models from isolated, engineer-specific tools into robust, cloud-native services that are scalable and consistently available. Our approach is firmly rooted in Kubernetes, positioning our team at the cutting edge of cloud solutions.

We are seeking a highly skilled and motivated Senior Machine Learning Engineer to join our team in Australia. The successful candidate will have a strong background in machine learning and software engineering, with experience in developing and deploying machine learning models in real-world applications. The ideal candidate will have a passion for working with data, a strong understanding of machine learning algorithms and techniques, cloud technology and the ability to communicate complex technical concepts to stakeholders.

This position is based in Sri Lanka.

What You Will Do

As a Senior Machine Learning Engineer, you will work closely with technical teams on the customer side and Customer Success, Enterprise Support, and Product Engineering teams on the H2O side.

Your primary responsibilities are:

Deliver technical professional services to the customer.
Working closely with H2O Data Scientists in advising and developing end to end machine learning solutions for the customer requirements.
Integrating H2O products with customer data sources for model training.
Integrating machine learning models/pipelines (python and mojo scoring pipelines) with customer systems for scoring (relatime/batch) as well as model monitoring and operations.
Implementing end to end MLdata flow pipelines that help streamline and data science solutions to a business problem.
Implementing AI driven applications using the open source H2O Wave SDK.
Provide/gather customer feedback so that you can work with the H2O.ai Engineering team to further enhance our products for needed features.
Ensure the scalability, reliability, and performance of deployed models by implementing appropriate monitoring, testing, and debugging processes.
Work on GenAI tools - LLMs, Agents, Fine tuning engines, RAG, create GenAI Apps

Your additional responsibilities include:

Be the trusted solutions advisor for our customers and partners.
Communicate effectively with a diverse audience of internal and external stakeholders consisting of: Engineers, business people, partners, executives.
Translate business cases and requirements into value based technical solutions through the architecture of machine learning workflows and systems from data ingestion to model deployment.

What We Are Looking For

Bachelor’s or a higher education degree in Computer Science/Engineering, data science, statistics or related field

Data Engineering Skills

Experience building data pipelines, ETL data sets, preferably on ‘Big Data’
Excellent understanding and experience with big data tools like Hadoop and Spark
Excellent knowledge of SQL query language and working with relational databases.
Understanding of various NoSQL database types and their application scenarios
Experience in Spark/Kafka and Hadoop ecosystem

Programming Languages/Frameworks

Proficient in Python or R for data science. Java, Bash scripting, Scala Go are a plus
Experience with writing REST API using microservices frameworks in Python or Java
Experience in building and deploying agentic/RAG AI applications
Experience with dockerization of services (i.e. creating docker images)
Understanding of Kubernetes based application development

Data Science skills

Experience of visualizing and presenting (EDA) to stakeholders using H2O Wave (plus), or other standard data visualization libraries in the Python and R stacks or using Tableau/PowerBi.
Experience with post production model monitoring tools like H2O MLOps (plus) MLFlow etc.
Understanding of using a variety of machine learning techniques (supervised/unsupervised, clustering,
decision tree learning, neural networks, etc.) and their real-world advantages/drawbacks/tuning
techniques.
Understanding of using advanced statistical techniques and concepts (regression, properties of distributions, statistical tests and proper usage, etc.) for practical applications.

Additional Requirements

Experience of working in a customer-facing environment, providing technical services
Excellent communication skills (proficient in spoken and written English). Additional languages are a plus.
Amicable attitude. Aptitude to independently investigate and find solutions to technical problems; urge to learn/master new technologies. Maker mindset.

How to Stand Out From the Crowd

Experience with big data technologies such as Hadoop, Spark, or NoSQL databases.
Experience in designing & building multi-agents frameworks and solutions
Familiarity with DevOps practices and tools such as Git, Jenkins, ArgoCD.
Knowledge of data privacy and security principles.
Experience with natural language processing or computer vision tasks.
Experience with model interpretability techniques such as feature importance, partial dependence plots, or SHAP values.
Experience with IaC technologies such as Terraform, AWS Cloud Formation.
Experience with containerization technologies such as Kubernetes, Docker.
Experience of debugging/troubleshooting containerized workloads and familiarity with tools such as kubectl, helm etc.

Why H2O.ai?

Market leader in total rewards
Remote-friendly culture
Flexible working environment
Be part of a world-class team
Career growth

H2O.ai is committed to creating a diverse and inclusive culture. All qualified applicants will receive consideration for employment without regard to their race, ethnicity, religion, gender, sexual orientation, age, disability status or any other legally protected basis.

H2O.ai is an innovative AI cloud platform company, leading the mission to democratize AI for everyone. Thousands of organizations from all over the world have used our cutting-edge technology across a variety of industries. We’ve made it easy for people at all levels to generate breakthrough solutions to complex business problems and advance the discovery of new ideas and revenue streams. We push the boundaries of what is possible with artificial intelligence.

H2O.ai employs the world’s top Kaggle Grandmasters, the community of best-in-the-world machine learning practitioners and data scientists. A strong AI for Good ethos and responsible AI drive the company’s purpose.

Please visit www.H2O.ai to learn more.
#LI-Hybrid

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Who We Are

Having surpassed $200M ARR and continuing to grow, AuditBoard is the leading audit, risk, ESG, and InfoSec platform on the market. More than 50% of the Fortune 500, including 7 of the Fortune 10, leverage our award-winning technology to move their businesses forward with greater clarity and agility. And our customers love us: AuditBoard is top-rated on G2.com and Gartner Peer Insights.

At AuditBoard, we inspire each other to innovate and are proud of what we are producing. We spend each day thinking of new ways to help our customers and contribute to the greater good of our company and our surrounding communities. We are all about assisting each other and breaking through barriers to create the most loved audit, risk, ESG, and InfoSec platform by our customers. This is how we have become one of the 500 fastest-growing tech companies in North America for the sixth year in a row, as ranked by Deloitte!

Why This Role is Exciting

We are seeking a passionate and skilled Machine Learning Engineer to join our effort to push the frontiers of risk management. This role offers the opportunity to work with cutting-edge Large Language Models (LLMs), utilizing techniques like Retrieval-Augmented Generation (RAG), Few-Shot Learning, Prompt Engineering, Fine-Tuning, Semantic Search, and Knowledge Distillation, etc. You will apply your expertise to build advanced AI/ML solutions, enhancing our AuditBoard product portfolio with features like predictive analytics, automated risk assessments, intelligent data extraction, and personalized insights. If you're excited about leveraging modern AI/ML techniques to transform the industry, this role is for you. Join our customer-focused team dedicated to continuous learning and innovation.

Responsibilities

Build, ship, and own product features end-to-end such as predictive analytics, automated risk assessments, intelligent data extraction, and personalized insights.
Work with engineers, designers, and product managers to create high-performing product features.
Design and implement AI solutions using classical ML methods and advanced techniques like LLMs
Write well-designed, maintainable, and testable code
Write clear and well-defined design documentation
Troubleshoot, debug, and resolve software bugs
Be product-minded and think about the customer
Stay updated on AI/ML advancements and explore new techniques and tools.
Participate in an Agile software development life cycle
Work with Python, JavaScript, Node.JS, Docker, PostgreSQL, Kubernetes, etc

Attributes of a Successful Candidate:

Bachelor’s or Master’s degree in Computer Science, Statistics, Mathematics, or a related field
4 plus years of hands-on experience in developing and deploying machine learning models
Ability to write scalable production-quality code
Proficiency in classical machine learning methods and familiarity with newer techniques like LLMs
Excellent programming skills in Python, Java, or similar languages
Experience with machine learning frameworks such as TensorFlow, PyTorch, Hugging Face, Keras, MXNet, or scikit-learn.
Familiarity with search/information retrieval, and ranking systems
Strong communication skills and ability to work collaboratively
Analytically minded with a focus on metrics and evaluation
Motivation to work hard and always be learning

Preferred

Experience with Node.JS and modern ES6 or TypeScript
Experience working on SaaS web applications
Basic understanding of distributed systems
Bonus: Docker, Kubernetes experience, AWS/Azure cloud infrastructure

Our Company Values

Customer obsession: Apply relentless focus on listening to and understanding customers as the core of everything we do
Win, together: Drive to be the best while supporting each other’s success
Gritty resilience: Thrive in a fast-paced and dynamic environment, balancing immediate priorities with big-picture strategic goals
Personal improvement: Stay eager to share insights, seek feedback, and continuously learn
Constant innovation: Challenge the status quo and drive improvements

Perks*

Launch a career at one of the fastest-growing SaaS companies in North America!
Live your best life (LYBL)! $200/mo for anything that enhances your life
Remote and hybrid work options, plus lunch in the Cerritos office
Comprehensive employee health coverage (all locations)
401K with match (US) or pension with match (UK)
Competitive compensation & bonus program
Flexible Vacation (US exempt & CA) or 25 days (UK)
Time off for your birthday & volunteering
Employee resource groups
Opportunities for team and company-wide get-togethers!

*perks may vary based on eligibility/location

Please note that background checks are required. Qualified Applicants with arrest or conviction records will be considered for Employment in accordance with the Los Angeles County Fair Chance Ordinance for Employers and the California Fair Chance Act. This role may have access to highly sensitive data, including employee data, customer data, company financials, and proprietary product information.

#LI-Remote

","hiringOrganization":{"@type":"Organization","name":"AuditBoard","sameAs":"https://auditboard.com/"},"jobLocation":{"@type":"Place","address":{"@type":"PostalAddress","addressLocality":"Canada","addressCountry":"Canada","addressRegion":"North America"}}}},{"@type":"ListItem","position":20,"item":{"@type":"JobPosting","title":"Senior Machine Learning Engineer","datePosted":"2025-08-08","description":"Meta Platforms, Inc. (Meta), formerly known as Facebook Inc., builds technologies that help people connect, find communities, and grow businesses. When Facebook launched in 2004, it changed the way people connect. Apps and services like Messenger, Instagram, and WhatsApp further empowered billions around the world. Now, Meta is moving beyond 2D screens toward immersive experiences like augmented and virtual reality to help build the next evolution in social technology. To apply, click “Apply to Job” online on this web page.Senior Machine Learning Engineer Responsibilities

Lead a team of engineers to build the recommendation product of Short Videos in Facebook Newsfeed, help them unblock, and advocate for ML excellence.
Architect, design, implement, and test large-scale distributed recommendation systems end-to-end (including inventory design, content retrieval, ranking stages, delivery, & ML infra) leveraging artificial intelligence, machine learning, deep learning, reinforcement learning, neural networks, data regression.
Develop ML models, ML systems, ML infrastructure and software applications using Python, C++, PHP, Hack, shell scripts, PyTorch, TensorFlow, Spark, Presto.
Adapt standard machine learning methods to best exploit modern parallel environments including distributed clusters, multi core SMP, and GPU.
Interface with 5+ cross-functional teams and partner teams of data scientists, product managers, frontend engineers, systems/infra engineers to collaborate on and launch cross-organizational projects.

Minimum Qualifications

Bachelor’s degree (or foreign equivalent) in Information Technology, Computer Science, or related field and 1 year of experience in the job offered or in a computer-related occupation.
Requires 1 year of experience in the following:
1. Machine Learning Framework(s): PyTorch, MXNet, or Tensorflow
2. Machine learning, recommendation systems, ranking systems, computer vision, natural language processing, data mining, or distributed systems
3. Translating insights into business recommendations
4. Hadoop/HBase/Pig or MapReduce/Sawzall/Bigtable/Spark
5. Developing and debugging in programming languages: C/C++, Java, Perl, Python, PHP, Haskell, and/or Shell Scripts
6. Relational databases and SQL
7. Linux, UNIX, or other *nix-like OS including file manipulation and simple commands
8. Building highly-scalable performant solutions
9. Distributed systems including sharding, consistency, and availability and
10. Data structures and algorithms
11. Developing machine learning ranking models with Two Tower Sparse Neural Networks, Multi-Task Multi-Label Neural Networks, and ID-based Two Tower Models
12. Recommendation and ML technologies including Collaborative Filtering, Maximal Marginal Relevance, and Determinantal Point Processes
13. A/B testing and experimentation analysis

For those who live in or expect to work from California if hired for this position, please click here for additional information. About Meta Meta builds technologies that help people connect, find communities, and grow businesses. When Facebook launched in 2004, it changed the way people connect. Apps like Messenger, Instagram and WhatsApp further empowered billions around the world. Now, Meta is moving beyond 2D screens toward immersive experiences like augmented and virtual reality to help build the next evolution in social technology. People who choose to build their careers by building with us at Meta help shape a future that will take us beyond what digital connection makes possible today—beyond the constraints of screens, the limits of distance, and even the rules of physics.
$222,772/year to $240,240/year + bonus + equity + benefits

Individual compensation is determined by skills, qualifications, experience, and location. Compensation details listed in this posting reflect the base hourly rate, monthly rate, or annual salary only, and do not include bonus, equity or sales incentives, if applicable. In addition to base compensation, Meta offers benefits. Learn more about benefits at Meta.

Equal Employment Opportunity Meta is proud to be an Equal Employment Opportunity employer. We do not discriminate based upon race, religion, color, national origin, sex (including pregnancy, childbirth, reproductive health decisions, or related medical conditions), sexual orientation, gender identity, gender expression, age, status as a protected veteran, status as an individual with a disability, genetic information, political views or activity, or other applicable legally protected characteristics. You may view our Equal Employment Opportunity notice here. Meta is committed to providing reasonable accommodations for qualified individuals with disabilities and disabled veterans in our job application procedures. If you need assistance or an accommodation due to a disability, fill out the Accommodations request form.","hiringOrganization":{"@type":"Organization","name":"Meta","sameAs":"https://www.meta.com/"},"jobLocation":{"@type":"Place","address":{"@type":"PostalAddress","addressLocality":"Menlo Park, CA","addressCountry":"United States","addressRegion":"North America"}}}},{"@type":"ListItem","position":21,"item":{"@type":"JobPosting","title":"Senior Machine Learning Engineer","datePosted":"2025-08-07","description":"

Job Description

Senior ML Engineer - AI Agents

Zendesk’s people have one goal in mind: to make Customer Experience better. Our products help more than 125,000 global brands (AirBnb, Uber, JetBrains, Slack, among others) make their billions of customers happy, every day.

Our team is dedicated to providing a state-of-the-art retrieval-augmented generation (RAG) platform across multiple channels; including customer service bots, email and search. In collaboration with ML scientists, we deliver high-quality AI products leveraging the latest tools and techniques, and serve them at a scale that most companies can only dream of. We’re passionate about empowering end-users to quickly find answers to their questions, and helping our customers make the most of their knowledge base.

We’re looking for a Senior ML engineer to join our team and play a key role in levelling up the RAG platform powering Zendesk!

What you’ll be doing

Delivering AI-powered capabilities to our customers at Zendesk scale using the latest in LLM technology
Working closely with Product Management, ML Scientists and other ML Engineers to define feature scope and implementation strategies
Mentoring junior team members, as well as pairing with more experienced colleagues to foster mutual learning
Supporting our deployed services to ensure a high level of stability and reliability
Contributing to discussions regarding technical design and best practices
Writing clean and maintainable code to meet the team’s delivery commitments

Here some of the challenges you will be working on:
- How do we best expand our RAG platform to handle new use cases?
- How do we optimize our system for both speed and cost-efficiency?
- How do we incorporate multiple sources of context to improve the accuracy of our generated answers?
- How do we make the best use of rapidly evolving LLM technologies?
- And many more!

What you bring to the role

Basic Qualifications

4+ years developing machine learning systems in Python
Solid understanding of architecture and software design patterns for server-side applications

Experience with managing and deploying cloud services with a cloud provider (AWS, GCP, Azure)

Experience building scalable and stable software applications
Collaborative and growth mindset, with a commitment to ongoing learning and development
Self-managed and agile, with the ability to problem-solve independently

Excellent communication skills, both written and verbal

Preferred Qualifications

Experience with using LLMs at scale
Experience in designing and implementing RAG systems
Experience with managing and deploying cloud services with AWS
Proven experience making data-driven engineering decisions; formulating hypotheses, conducting experiments, and analyzing results.

What our tech stack looks like

Our code is largely written in Python, with some parts in Ruby
Our platform is built on AWS
Data is stored in RDS MySQL, Redis, S3, ElasticSearch, Kafka, and Athena
Services are deployed to Kubernetes using Docker, with Kafka for stream processing
Infrastructure health is monitored using Datadog and Sentry

What we offer

Team of passionate people who love what they do!
Exciting opportunity to work with LLMs and RAG (retrieval augmented generation), rapidly evolving fields in AI
Ownership of the product features at scale, making a significant impact for millions of customers
Opportunity to learn and grow!
Possibility to specialise in areas such as security, performance, and reliability

...and everything you need to be effective and maintain work-life balance

Flexible working hours
Professional development funds
Comfortable office and a remote-friendly environment

#LI-AO1

The intelligent heart of customer experience

Zendesk software was built to bring a sense of calm to the chaotic world of customer service. Today we power billions of conversations with brands you know and love.

Zendesk believes in offering our people a fulfilling and inclusive experience. Our hybrid way of working, enables us to purposefully come together in person, at one of our many Zendesk offices around the world, to connect, collaborate and learn whilst also giving our people the flexibility to work remotely for part of the week.

Zendesk is an equal opportunity employer, and we’re proud of our ongoing efforts to foster global diversity, equity, & inclusion in the workplace. Individuals seeking employment and employees at Zendesk are considered without regard to race, color, religion, national origin, age, sex, gender, gender identity, gender expression, sexual orientation, marital status, medical condition, ancestry, disability, military or veteran status, or any other characteristic protected by applicable law. We are an AA/EEO/Veterans/Disabled employer. If you are based in the United States and would like more information about your EEO rights under the law, please click here.

Zendesk endeavors to make reasonable accommodations for applicants with disabilities and disabled veterans pursuant to applicable federal and state law. If you are an individual with a disability and require a reasonable accommodation to submit this application, complete any pre-employment testing, or otherwise participate in the employee selection process, please send an e-mail to peopleandplaces@zendesk.com with your specific accommodation request.

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📍Location: Remote (Spain-based)

📈 Level: Senior

🔗Type: Full-time

At Nuvolar, we’re driven by purpose, integrity, and the pursuit of excellence, and we’re looking for a Senior Machine Learning Engineer who shares these values to join an ambitious and impactful project in the healthcare industry.

You'll play a key role in transforming complex data into life-changing solutions. This is more than just a technical role: it's a chance to make a tangible difference in the way healthcare works, and in people’s lives.

🧠 What You’ll Do

As part of a dynamic, cross-functional team, you’ll be responsible for designing, building, and deploying production-ready machine learning models and robust data pipelines in Microsoft Azure. You’ll collaborate with both technical peers and business stakeholders to develop innovative, data-driven solutions with real-world healthcare applications.

Your main responsibilities will include:

Develop, train, evaluate, and deploy predictive data models using Python and ML libraries such as Scikit-learn and PyTorch.
Design, build, and maintain scalable data processing pipelines and data flows using Azure Data Factory (ADF).
Utilize Azure ML Studio for model experimentation, training, and deployment.
Work extensively with large datasets, including Parquet files, stored in Azure Data Lake.
Perform feature engineering and selection to optimize model performance.
Define and apply appropriate validation metrics (e.g., accuracy, precision, recall, F1-score) to assess model performance and ensure business alignment.
Collaborate with stakeholders to understand business needs and translate them into technical requirements, even when dealing with ambiguous or non-detailed user stories.
Effectively communicate technical concepts and model outcomes to both technical and non-technical audiences.
Contribute to the design and architecture of cloud-based data science applications.
Manage code and collaborate with the team using Git, and perform tasks using Bash and the command line.
Develop and deploy serverless components using Azure Function Apps.

✅ What We’re Looking For

We’re seeking someone with strong technical expertise, business acumen, and a proactive mindset who thrives in collaborative environments.

Must-haves:

5+ years of experience in data science or ML engineering.
Solid experience with the Azure cloud ecosystem: ADF, ML Studio, Data Lake.
Deep Python knowledge and experience with Pandas, NumPy, Scikit-learn, and PyTorch.
Strong SQL skills and familiarity with data formats like Parquet.
Proficient with Git, Bash, and working in terminal environments.
Ability to work independently with minimal direction on complex tasks.
Excellent communication skills in English – both written and spoken.

Nice-to-haves:

Experience training or fine-tuning generative models (e.g., LLMs).
Advanced knowledge of serverless architectures and Azure Function Apps.

💜 Why You’ll Love Working at Nuvolar

Impactful Projects: You’ll work on meaningful projects that improve real lives in the healthcare space.
People-First Culture: We care about our team, support each other, and have fun together.
Remote-First Approach: Work from anywhere with flexibility and trust. Enjoy every other Friday off and the summer schedule in July and August.
Continuous learning – Access training programs, mentorship, and career development opportunities, and an annual budget for professional development.
Health and wellness perks – Private health insurance and a gym subsidy.
Great company culture – We organize team events, knowledge-sharing sessions, and fun activities!

The Hiring Process

We like to keep things simple and transparent:

\n
HR Interview – A friendly conversation with our HR team to understand your background and career aspirations.
\n
\n
Technical challenge – A hands-on task to assess your problem-solving skills.
\n
\n
Technical interview – Meet the team and discuss your approach to data engineering.
\n

If you’re ready to take the next step in your career and work on exciting data projects, apply now! 🚀

To be aware of all of our latest updates, follow us via LinkedIn | Instagram | Glassdoor | Medium

Nuvolar Works is an equal-opportunity employer and will not discriminate against any applicant based on age, gender, sexual orientation, disability, national origin, race, or religion. Candidates with disabilities are encouraged to apply, and we are committed to providing an inclusive and accessible recruitment process.

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We’re looking for a Machine Learning Engineer to help us accomplish our mission to improve and extend lives by learning from the experience of every person with cancer. Are you ready to be the next changemaker in cancer care?

Flatiron Health is a healthtech company using data for good to power smarter care for every person with cancer, around the world. Flatiron partners with cancer centers in the US, Europe and Asia to transform patients’ real-life experiences into real-world evidence and create a more modern, connected oncology ecosystem. Our multidisciplinary teams include oncologists, data scientists, software engineers, epidemiologists, product experts and more. Flatiron Health is an independent affiliate of the Roche Group.

What You'll Do

At Flatiron, we’re advancing the use of machine learning, generative AI, and natural language processing to extract clinically relevant information from unstructured medical notes for use in oncology research. The Data Curation team is helping to build these next generation research data products, developing and applying ML models to capture a complete picture of the patient journey

As part of our team, you will develop and validate models to solve applied clinical problems and help build towards our vision of the future of machine learning at Flatiron. Engaging with a cross-functional group of stakeholders across our teams in Europe, Japan, and the US you will contribute to model development projects from scoping through to productionization and delivery.

In addition, you'll also:

Interface with internal scientific stakeholders and customers to understand what data they need to conduct high quality research.
Build models to turn raw clinical data into high quality research variables, drawing on your knowledge of LLMs, traditional ML, and NLP techniques to determine the right methods to use for a given problem.
Work with quantitative scientists and oncologists to validate that your models can be used to generate sound scientific insights.
Collaborate with other Data Scientists to accelerate our ML capabilities and develop novel approaches to clinical data extraction from unstructured health records.
Work cross-functionally with software engineers to productionize, scale, and monitor your models.

Who You Are

You're a product-focused data scientist, with experience in leveraging ML and NLP to solve real-world problems. You're excited by the prospect of rolling up your sleeves to tackle meaningful problems each and every day. You’re a kind, passionate and collaborative problem-solver who seeks and gives candid feedback, and values the chance to make an important impact.

You have 5+ years of relevant working experience in a technical capacity, with a focus on ML. Prior experience with NLP and LLMs is strongly preferred.
You have a strong background in applying ML to solve real-world problems and a solid grasp of the underlying statistical fundamentals of ML.
You are excited to work in a startup environment, think creatively and be scrappy to get the job done. You have a nose for value and empathy for your customers
You have collaborated with other technical team members in a production development environment using formal version control, Python, and SQL.

Optional:

You have ML experience in a healthcare setting.
You have experience with the risks of bias in machine learning, health equity research/analysis or have worked with underrepresented groups in a clinical research setting.

If this sounds like you, you'll fit right in at Flatiron.

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While technology is the heart of our business, a global and diverse culture is the heart of our success. We love our people and we take pride in catering them to a culture built on transparency, diversity, integrity, learning and growth.

If working in an environment that encourages you to innovate and excel, not just in professional but personal life, interests you- you would enjoy your career with Quantiphi!

Experience (in Years) : 4 to 10 years.

Location: Bangalore, Mumbai & Trivandrum

Roles and Responsibilities

Good analytical skills, with expertise in analytical tool-kits such as Logistic Regression, Cluster Analysis, Factor Analysis, Multivariate Regression, Statistical modelling, predictive analysis.
Hands-on with Python/R programming and knowledge of machine learning tools like Scikit-Learn, Pandas, TensorFlow, Pytorch, Keras, OpenCV, XGBoost etc.
Computer Vision: Image preprocessing, image matching/comparison using SIFT/SURF/ORB, Object detection (Faster RCNN, YOLO, SSD, etc.), Image similarity (Siamese network), Image classification.
NLP: Vector Space modeling in NLP, LSTMS, Sequence modeling, Attention modeling, BERT, Transformers. Using the above mentioned techniques performing Document classification, Semantic similarity, NER, Sentiment Analysis.
Time Series Analysis using ARIMA, SARIMA, LSTMs, etc.
Knowledge of statistical modelling and popular machine learning models.
Feature engineering, Feature selection/Feature importance, Dimensionality
Reduction (PCA, etc.), Hyperparameter tuning, Ensembling techniques like Bagging, Boosting, Stacking.
Should possess knowledge of multiple cloud platforms (GCP-Preferable, Azure or AWS) and machine learning services offered by them.
Critical eye for the quality of data and strong desire to get it right.
A pleasantly forceful personality and charismatic communication style. Skills- Required
Experience in building end to end machine learning pipelines, deployment using any ML Ops Framework (Kube Flow Pipelines, Vertex AI), model performance monitoring, CI/CD.
Experience in GCP based ML solutions and services like Contact Center AI, Vertex AI, Document AI, Speech-to-Text, Text-to Speech, Natural Language, Dialog Flow, AutoML, Vision, Video Intelligence, Base OCR, Form Parser, Invoice Parser, etc
Ability to multitask and work on multiple engagements related to different domains.
Be able to pick up newer technologies in a short span of time.
Work in a highly collaborative environment by interacting with the stakeholders and various IT teams within the company to facilitate design and development of ML/AI solutions.
Be responsible for the successful delivery of all allocated projects with respect to schedule, quality and customer satisfaction.
Follow Agile standards and methodologies in all phases of the project.
Ensure excellence in delivery to customers.
Self-driven individuals with a passion for research and development and the zest for solving what matters.

If you like wild growth and working with happy, enthusiastic over-achievers, you'll enjoy your career with us!

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WHO WE ARE 🌍

Manychat is a leading Chat Marketing platform. We help businesses engage with their customers on Instagram, TikTok, Facebook Messenger, WhatsApp, and more.

Trusted by over 1 million brands in 170+ countries, we're an official Meta Business Partner, backed by top investors, including Summit Partners and BVP.

With 300+ teammates across international offices in Austin, Barcelona, Yerevan, São Paulo, and Amsterdam — Manychat helps creators and businesses across the globe grow faster, engage better and sell more on social and messaging apps.

WHO WE'RE LOOKING FOR 🌟

Manychat automates millions of conversations each day, helping to build connections and drive value for over a million creators and businesses around the world. We're seeking an experienced Machine Learning Engineer to join our ML and AI squad, and help us translate our rich data into helpful, delightful, and valuable user experiences.

Reporting to the Head of Data, you’ll work closely with ML scientists and Data engineers to translate ML and AI models into reliable, scalable machine learning solutions. This is a high-impact role that blends engineering excellence with Machine Learning innovation.

WHAT YOU'LL DO 🚀

\n
- Design, develop, and deploy ,in collaboration with ML Scientists and Data Engineers, production level machine learning models and AI applications.
- Ensure scalability, efficiency, and accuracy of deployed ML and AI models
- Evaluate potential architecture solutions and tooling.
- Maintain clean, reproducible, and scalable ML code and pipelines.
- Drive a strong MLOps culture standardizing best practices for CI/CD, model governance, observability, and reliability
\n
- Participate in code reviews and knowledge sharing within the team
\n

WHAT YOU’LL BRING 💥

6+ years of proven experience as a Machine Learning Engineer, or equivalent.
Highly proficient in Python, and good knowledge of SQL. An additional strongly typed language is a plus.
Demonstrated experience in the principles of ML.
Experience building, testing, deploying, monitoring, and maintaining ML in production.
Cloud and data infrastructure experience (e.g., AWS, Snowflake, Sagemaker, Redis)
Experience in integrating new Machine Learning tooling, core frameworks (e.g. PyTorch/TensorFlow), orchestration (e.g. Airflow), and containerisation (e.g. Docker/K8s).
Experience in building MLOps tooling and processes.
Track record of project leadership, cross-team collaboration, and coordination with Product Managers and Engineering teams.
Bonus points for knowledge and experience in building, testing, deploying, monitoring, and maintaining LLM models (Prompt engineering, RAG, Fine tuning, LLM ops tooling).

WHAT WE OFFER 🤗

We care deeply about your growth, well-being, and comfort:

🌍 Hybrid onboarding to start work remotely and relocation support for you and your family.
💙 Comprehensive health insurance for both you and your family.
📚 Professional development budget for conference tickets, online courses, and other relevant resources to help you grow.
🫶 Flexible benefits package to tailor perks that matters most for you.
🪴 Hybrid work and generous leave options to prioritize your work-life balance.
🍽️ In-office perks, including free meals and snacks.
🤝 Company-funded sport activities, annual offsites and team-building events.

Manychat is an Equal Opportunity Employer. We’re committed to building a diverse and inclusive team. We do not discriminate against qualified employees or applicants because of race, color, religion, gender identity, sex, sexual preference, sexual identity, pregnancy, national origin, ancestry, citizenship, age, marital status, physical disability, mental disability, medical condition, military status, or any other characteristic protected by local law or ordinance.

This commitment is also reflected through our candidate experience. If you have individual needs that may require an accommodation during the interview process, please indicate this in your application. We will do our best to provide assistance throughout your interview process to ensure you’re set up for success.

With my application, I accept the Manychat Privacy Policy.

","hiringOrganization":{"@type":"Organization","name":"Manychat","sameAs":"https://manychat.com/"},"jobLocation":{"@type":"Place","address":{"@type":"PostalAddress","addressLocality":"Barcelona, Spain","addressCountry":"Spain","addressRegion":"Europe"}}}},{"@type":"ListItem","position":26,"item":{"@type":"JobPosting","title":"Senior Machine Learning Engineer","datePosted":"2025-08-06","description":"

WHO WE ARE 🌍

Manychat is a leading Chat Marketing platform. We help businesses engage with their customers on Instagram, TikTok, Facebook Messenger, WhatsApp, and more.

Trusted by over 1 million brands in 170+ countries, we're an official Meta Business Partner, backed by top investors, including Summit Partners and BVP.

WHO WE'RE LOOKING FOR 🌟

WHAT YOU'LL DO 🚀

\n
- Design, develop, and deploy ,in collaboration with ML Scientists and Data Engineers, production level machine learning models and AI applications.
- Ensure scalability, efficiency, and accuracy of deployed ML and AI models
- Evaluate potential architecture solutions and tooling.
- Maintain clean, reproducible, and scalable ML code and pipelines.
- Drive a strong MLOps culture standardizing best practices for CI/CD, model governance, observability, and reliability
\n
- Participate in code reviews and knowledge sharing within the team
\n

WHAT YOU’LL BRING 💥

6+ years of proven experience as a Machine Learning Engineer, or equivalent.
Highly proficient in Python, and good knowledge of SQL. An additional strongly typed language is a plus.
Demonstrated experience in the principles of ML.
Experience building, testing, deploying, monitoring, and maintaining ML in production.
Cloud and data infrastructure experience (e.g., AWS, Snowflake, Sagemaker, Redis)
Experience in integrating new Machine Learning tooling, core frameworks (e.g. PyTorch/TensorFlow), orchestration (e.g. Airflow), and containerisation (e.g. Docker/K8s).
Experience in building MLOps tooling and processes.
Track record of project leadership, cross-team collaboration, and coordination with Product Managers and Engineering teams.
Bonus points for knowledge and experience in building, testing, deploying, monitoring, and maintaining LLM models (Prompt engineering, RAG, Fine tuning, LLM ops tooling).

WHAT WE OFFER 🤗

We care deeply about your growth, well-being, and comfort:

🌍 Hybrid onboarding to start work remotely and relocation support for you and your family.
💙 Comprehensive health insurance for both you and your family.
📚 Professional development budget for conference tickets, online courses, and other relevant resources to help you grow.
🫶 Flexible benefits package to tailor perks that matters most for you.
🪴 Hybrid work and generous leave options to prioritize your work-life balance.
🍽️ In-office perks, including free meals and snacks.
🤝 Company-funded sport activities, annual offsites and team-building events.

","hiringOrganization":{"@type":"Organization","name":"Manychat","sameAs":"https://manychat.com/"},"jobLocation":{"@type":"Place","address":{"@type":"PostalAddress","addressLocality":"Amsterdam, Netherlands","addressCountry":"The Netherlands","addressRegion":"Europe"}}}},{"@type":"ListItem","position":27,"item":{"@type":"JobPosting","title":"Senior Machine Learning Engineer","datePosted":"2025-08-06","description":"

Your opportunity

As a crucial member of our team, you'll play a pivotal role across the entire machine learning lifecycle, contributing to our conversational AI bots, RAG system and traditional ML problem solving for our observability platform.

Your tasks will encompass both operational and engineering aspects, including building production-ready inference pipelines, deploying and versioning models, and implementing continuous validation processes.

On the LLM side you'll fine-tune generative AI models, design agentic language chains, and prototype recommender system experiments.

What you'll do

In this role, you'll have the opportunity to contribute significantly to our machine learning initiatives, shaping the future of AI-driven solutions in various domains. If you're passionate about pushing the boundaries of what's possible in machine learning and ready to take on diverse challenges, we encourage you to apply and join us in our journey towards innovation.

This role requires

Proficiency in software engineering design practices.
Experience working with transformer models and text embeddings.
Proven track record of deploying and managing ML models in production environments.
Familiarity with common ML/NLP libraries such as PyTorch, Tensorflow, HuggingFace Transformers, and SpaCy.
5+ years of developing production-grade applications in Python.
Proficiency in Kubernetes and containers.
Familiarity with concepts/libraries such as sklearn, kubeflow, argo, and seldon.
Expertise in Python, C++, Kotlin, or similar programming languages.
Experience designing, developing, and testing scalable distributed systems.
Familiarity with message broker systems (e.g., Kafka, RabbitMQ).
Knowledge of application instrumentation and monitoring practices.
Experience with ML workflow management, like AirFlow, Sagemaker, etc.
Fine-tuning generative AI models to enhance performance.
Designing AI Agents for conversational AI applications.
Experimenting with new techniques to develop models for observability use cases
Building and maintaining inference pipelines for efficient model deployment.
Managing deployment and model versioning pipelines for seamless updates.
Developing tooling to continuously validate models in production environments.

Bonus points if you have

Familiarity with the AWS ecosystem.
Past projects involving the construction of agentic language chains

Please note that visa sponsorship is not available for this position.

Fostering a diverse, welcoming and inclusive environment is important to us. We work hard to make everyone feel comfortable bringing their best, most authentic selves to work every day. We celebrate our talented Relics’ different backgrounds and abilities, and recognize the different paths they took to reach us – including nontraditional ones. Their experiences and perspectives inspire us to make our products and company the best they can be. We’re looking for people who feel connected to our mission and values, not just candidates who check off all the boxes.

If you require a reasonable accommodation to complete any part of the application or recruiting process, please reach out to resume@newrelic.com.

We believe in empowering all Relics to achieve professional and business success through a flexible workforce model. This model allows us to work in a variety of workplaces that best support our success, including fully office-based, fully remote, or hybrid.

Our hiring process

In compliance with applicable law, all persons hired will be required to verify identity and eligibility to work and to complete employment eligibility verification. Note: Our stewardship of the data of thousands of customers’ means that a criminal background check is required to join New Relic.

We will consider qualified applicants with arrest and conviction records based on individual circumstances and in accordance with applicable law including, but not limited to, the San Francisco Fair Chance Ordinance.

Headhunters and recruitment agencies may not submit resumes/CVs through this website or directly to managers. New Relic does not accept unsolicited headhunter and agency resumes, and will not pay fees to any third-party agency or company that does not have a signed agreement with New Relic.

Candidates are evaluated based on qualifications, regardless of race, religion, ethnicity, national origin, sex, sexual orientation, gender expression or identity, age, disability, neurodiversity, veteran or marital status, political viewpoint, or other legally protected characteristics.

Review our Applicant Privacy Notice at https://newrelic.com/termsandconditions/applicant-privacy-policy

","hiringOrganization":{"@type":"Organization","name":"New Relic","sameAs":"https://newrelic.com/"},"jobLocation":{"@type":"Place","address":{"@type":"PostalAddress","addressLocality":"Bangalore, India","addressCountry":"India","addressRegion":"Asia/Pacific"}}}},{"@type":"ListItem","position":28,"item":{"@type":"JobPosting","title":"Senior Machine Learning Engineer","datePosted":"2025-08-08","description":"

About TruckSmarter

Logistics is one of the single largest industries in the world. Globally, logistics is an $8-$12 trillion dollar industry and in the US alone, ~$2 trillion, representing ~10% of GDP. A single percent of improvement drives profound change to every corner of the world—from the cost of our goods, to the livelihoods of local communities, to even the impact on our environment. To reshape the industry, at TruckSmarter, our focus is first on truck drivers. Trucks move 71% of freight in America (~$800bn annually) & the trucking industry represents nearly 6% of the full-time jobs in the country. If you look around you, every item has sat on a truck at one point on its journey to you. However, despite the industry being one of the greatest levers of innovation throughout history, it is still deeply fragmented & structurally misaligned. Our mission is to fix that—and we need your help.

The Role

As one of our first Senior Machine Learning Engineer, you will be responsible for building machine learning models, the corresponding data pipelines and the local and production training and inference systems for our core product and operational workflows. You will work closely with designers, operations team, and other engineers driving the technical design, implementation and scale up.

Working model: TruckSmarter offers an in-office collaborative culture. This role is based out of our downtown San Francisco office, and requires in-office presence three days per week (typically Mondays, Wednesdays, and Fridays).

What Excites You

Define the AI/ML roadmap enabling Agentic AI as well as the traditional AI/ML models for identity verification, fraud detection, underwriting and dispatch products.
Own the delivery of key business, product and technology initiatives across design, specification, development, testing, and launch.
Establish and implement processes for model training, fine-tuning, testing, and operating the Generative AI models at significant scale.
Investigate, prototype and deliver innovative solutions.
Collaborate with other engineers, Product and Business Teams to identify new ways to improve our product and drive growth.
Establish a data-driven development culture by driving the definition, tracking, and operationalizing of feature, product, and company-level metrics.

What Excites Us

Master’s or PhD degree in Computer Science or a related field.
5+ years of experience with designing, building and scaling ML Training and real-time Inferencing systems.
Proficiency in Python with experience using machine learning frameworks such as scikit-learn, pandas, numpy, xgboost, and pytorch.
Prior experience using LLMs to build AI agents.
Excellent written and oral communication skills and the capability to drive cross-functional requirements with business, product, operations and engineering teams.

What Success Looks Like

Build an Agentic AI architecture incorporating reasoning, decisioning, and actioning in our products.
Build, monitor and update the AI agents used to perform different operations.
Establish the auto-evaluation and monitoring frameworks for AI agents and AI/ML models.
Find the right balance in the usage of regular code, traditional AI/ML models and LLM agents at each stage of product scale.
Use TruckSmarter’s proprietary and other third party data to build our first machine learning models to predict the likelihood of fraud, and underwrite credit for businesses to keep our NPAs very low.
Establish the data pipelines for offline training and real-time inference.

We Offer

Health, Dental & Vision Plans
Competitive Pay
401k
Unlimited PTO
Lunch + dinner daily
Commuter benefits

We would love to have you be a part of something special, and are excited to review your application.

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About Nabla

We are a team of entrepreneurs, clinicians and engineers committed to bringing back joy to the practice of medicine.

Together with a community of clinician innovators, we’ve harnessed the best of machine learning science to develop Nabla: the leading AI assistant that’s restoring the human connection at the heart of healthcare. By streamlining clinical documentation, Nabla is helping clinicians focus on matters most - patient care. Today, over 85,000 clinicians across 130+ healthcare organizations trust Nabla to support how they deliver care every day.

We’re at the start of an ambitious journey: Ambient listening, dictation, coding, and command capabilities are all converging into a proactive assistant that intuitively streamlines clinical and financial workflows.

Backed by a recent $70M Series C, we’re hiring to build the next generation of clinical AI and improve the lives of clinicians and patients everywhere.

This is a great time to join us!

The best of AI at the service of healthcare

Nabla’s phenomenal traction is the result of 3 years of diligent product development.

Our team, led by former Meta AI Research engineers, has consistently anticipated how AI can revolutionize healthcare delivery. The Machine Learning team continually leverages the latest advancements to unlock AI’s full potential in healthcare.

Yann LeCun, Meta’s Chief AI Scientist and Turing award winner, is an advisor to Nabla.

What You’ll Do

As a senior machine learning engineer, you’ll play a key role in redefining clinicians’ workflows, unlocking better care for patients, and ensuring Nabla remains at the forefront of AI innovation. You will take ownership of high-impact projects and contribute to the growth and maturity of our ML team and R&D processes.

Within a team of experts who have built large-scale production systems at Facebook, Google, and Microsoft, you will:

Lead ambitious ML projects, collaborating with multiple engineers to deliver impactful solutions.
Go beyond ambient scribing to fully redefine clinicians’ workflows with AI, unlocking transformative efficiencies and improved patient care.
Propose and guide experiments, model architectures, and data-labeling strategies to improve our speech-to-text, note generation, and normalization systems.
Implement, train, and deploy models in production, ensuring scalability and robustness in a live healthcare setting.
Optimize R&D processes, enabling the team to ship new models quickly and confidently as we scale.
Stay at the cutting edge of AI research, sharing expertise and fostering technical growth within the team.

To get a sense of the impact you’ll have:

Nabla processes 10 billion tokens/month with LLMs.
By the time you’ve read this posting, Nabla will have transcribed 100 new hours of live audio and generated 500 new clinical notes, saving 125 hours of doctor time.

Our Stack

Python for everything ML-related
Pytorch and Transformers for training
vLLM for inference
Google Cloud & Kubernetes for deployment
Calls to OpenAI GPT-4 when needed

Where You’ll Be Based

Our offices are based in Paris 3e (Arts & Métiers).
Remote policy: 1-2 days a week (with some flexibility). Possibility of working remotely 1-2 weeks once a year.

Your DNA

The ideal candidate will bring both technical depth and leadership experience to help Nabla revolutionize healthcare with AI.

Requirements:

Deep expertise in machine learning: You have extensive (5+ years) experience in training and deploying neural networks for real-world use cases.
Strong leadership skills: Proven ability to lead ML projects, collaborate across teams, and mentor junior engineers.
Advanced Python coding skills: You write clean, production-ready code.
Vision for AI in healthcare: Passion for going beyond the status quo to redefine workflows and unlock better care for patients.
Fluent in English: You communicate clearly and effectively.
Broader software engineering experience (infrastructure, front-end, etc.) is a plus.

Your Team

You will join the Core team (Machine Learning specialists) and collaborate closely with Product Managers and other engineering teams.

The Engineering team currently comprises 20 people across three domains:

Apps: Responsible for our web application and Chrome extension.
Platform: Handles infrastructure, back-end, and our API solution.
Core: Focuses on Machine Learning innovation and delivery.

As a senior team member, you will play a pivotal role in shaping our roadmap and mentoring teammates to achieve their best work.

Benefits

Just like we’re dedicated to supporting doctors’ well-being, ensuring yours is a top priority. We firmly believe that by prioritizing your well-being, we support you to excel in your work.

Here are the benefits you get when joining Nabla:

Stock ownership
100% healthcare coverage
Meal vouchers
Public transportation costs covered at 50%
Exercise class during the workday: Yoga, running, pilates, HITT
Unlimited budget for book purchases, so you can continue to learn about ML / Healthcare
Culture of trust & accountability — your output matters more than your clock-in time

Life at Nabla

When you become a part of our company, you join a team of excellence-driven, curious, and genuinely kind individuals. Together, we're committed to making clinicians' lives easier and improving healthcare experiences for everyone. We believe in a world where clinicians can focus on what they were trained to do - caring for their patients, and where no patient feels their visit was rushed.

We come to work excited to leverage AI to do more for clinicians. We’re obsessed with our users’ satisfaction and we actively seek out opportunities to engage one-on-one with clinicians to understand how Nabla can better help. We consistently look for ways to improve and do not shy away from doing the work to excel. Whether it’s a feature our users asked for, or a new article for our blog, we prioritize collaboration to deliver exceptional outcomes.

We love having fun as much as we love work. Our #nablabla channel is as active as our #feature-show-off channel, we exercise during the work day at least 3 times a week (yoga, running, pilates, or HIIT, your choice!), enjoy regular off-sites to gather the team, and travel to see each other in places like NY, Paris, San Francisco, and many other vibrant cities. Oh, and we’re constantly snacking on chocolate or nuts!

If this sounds like an environment you’ll thrive in, we look forward to reading your application!

Diversity & Inclusion

Diversity and inclusivity are fundamental values at Nabla. We embrace individuals from various backgrounds, including race, gender, educational history, sexual orientation, and beyond.

As an equal opportunity employer, we actively seek out and welcome applicants from diverse backgrounds, believing that a wide range of perspectives enriches our team and enhances our ability to innovate and thrive.

Avoid recruitment scams: Stay safe and informed

There is an active employment scam which is now using Nabla to collect personal information or financial scams. If you’re contacted by a Nabla recruiter, please ensure whomever is contacting you truly represents Nabla and is utilizing a nabla.com email address. We will never ask for the exchange of any money or credit card details during the recruitment process. Nabla utilizes a hiring platform for all applications; please be aware of any suspicious email activity from people who could be pretending to be recruiters or senior professionals at Nabla. You can find more information following this link.

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Leonardo.Ai is building one of the world’s highest-throughput Generative AI platforms, enabling millions of users, from beginners to professionals, to create high-quality images and videos with ease. Now part of the Canva family, we’re growing our global R&D team to deliver AI tools, products, and infrastructure that make creativity limitless for nearly a quarter of a billion users.

The Role:

We’re looking for a Senior Machine Learning Engineer to join our Platform Tribe, the team that provides the tools, infrastructure, and expertise that help every other product team at Leonardo move faster.

In this role, you’ll work at the intersection of Generative AI and MLOps. You’ll partner with researchers and engineers, be embedded in other teams for high-impact projects, and help design the pipelines, GPU infrastructure, and automation that transform cutting-edge research into production-ready features, making creativity accessible to millions of people.

Your work will have a direct and visible impact: you’ll enable teams across Leonardo to deliver AI-powered features faster, more reliably, and at scale.

What You’ll Do:

Generative AI & Inference:

Collaborate with researchers to bring new models from prototype to production and ensure they deliver meaningful value.

Build and maintain production pipelines for diffusion-based and related generative models (e.g. LoRA, ControlNet).
Optimise inference for speed, reliability, and efficiency using techniques such as quantisation, distillation, caching, and multi-GPU parallelism.
Tackle complex challenges like orchestrating multi-GPU video pipelines while ensuring systems are intuitive and maintainable.

MLOps & Infrastructure:

Develop and maintain automated MLOps pipelines covering training, deployment, monitoring, and retraining.
Build CI/CD workflows for machine learning that make handovers from research to production seamless and safe.
Create scalable data pipelines and storage solutions to support high-throughput workloads.
Set up clear monitoring and alerting for model performance (e.g. Prometheus, Grafana, CloudWatch).
Design secure, reliable infrastructure on AWS (S3, EC2, SageMaker) using Infrastructure-as-Code tools like Terraform.

Platform Acceleration:

Be embedded in other teams, from Generations to Enterprise, to support high-impact projects requiring deep ML expertise.
Develop shared tooling, reusable workflows, and architecture patterns that help teams across Leonardo build and ship faster.
Promote knowledge-sharing, best practices, and scalable solutions across the organisation.

Skills We Love:

Generative AI Experience: Experience deploying diffusion-based or similar generative models into production and working with inference optimisation techniques.
MLOps Expertise: Skilled in building automated, reliable workflows for training, deploying, and monitoring ML models at scale.
Infrastructure & Cloud: Hands-on with AWS (S3, EC2, SageMaker), Kubernetes, Docker, and Infrastructure-as-Code (Terraform).
Performance & Efficiency: Proficient in techniques such as quantisation, distillation, caching, and distributed inference.
Data Foundations: Ability to design scalable data pipelines and storage solutions (SQL/NoSQL).
Engineering Craft: Strong Python skills and a focus on writing clear, maintainable, and collaborative code.
Collaboration & Growth: Thrive in cross-functional teams, value open feedback, and enjoy supporting others’ success while learning continuously.

Our Culture:

Inclusive Culture: We celebrate diversity and are committed to creating an inclusive environment where everyone feels valued and empowered. At Leonardo AI, your unique perspectives and experiences are welcomed and essential to our success.
Flexible Work Environment: We understand the importance of work-life balance. Enjoy the flexibility to work remotely or from our vibrant offices. We have employees all over the world, ensuring you can thrive personally and professionally.
Empowering Growth: Your development is our priority. We offer continuous learning opportunities and career growth tailored to your goals. You’ll be encouraged to grow and excel in your career at Leonardo AI.
Impactful Work: Join us in shaping the future of AI. You'll work on innovative projects that have a meaningful impact, and your contributions will help drive advancements in AI creativity.

Leonardo.Ai Benefits:

A range of benefits to set you up for every success in and outside of work. Here's a taste of what's on offer:
Impact the future of AI
Reward package including equity - we want our success to be yours too
Inclusive parental leave policy that supports all parents & carers with 18 weeks paid leave
An annual Vibe & Thrive allowance to support your wellbeing, social connection, office setup & more
Flexible leave options that empower you to be a force for good, take time to recharge and support you personally, including remote working abroad
Support with your professional development
Fun and engaging company events, both virtual and in-person
20 days annual leave

Please apply…

We’re realistic about experience, even if you haven’t worked at this scale before. We encourage anyone exposed to deploying generative models to production, working with techniques like LoRA or diffusion, and optimising inference across GPUs to apply for this role.

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The Role:

Your work will have a direct and visible impact: you’ll enable teams across Leonardo to deliver AI-powered features faster, more reliably, and at scale.

What You’ll Do:

Generative AI & Inference:

Collaborate with researchers to bring new models from prototype to production and ensure they deliver meaningful value.

Build and maintain production pipelines for diffusion-based and related generative models (e.g. LoRA, ControlNet).
Optimise inference for speed, reliability, and efficiency using techniques such as quantisation, distillation, caching, and multi-GPU parallelism.
Tackle complex challenges like orchestrating multi-GPU video pipelines while ensuring systems are intuitive and maintainable.

MLOps & Infrastructure:

Develop and maintain automated MLOps pipelines covering training, deployment, monitoring, and retraining.
Build CI/CD workflows for machine learning that make handovers from research to production seamless and safe.
Create scalable data pipelines and storage solutions to support high-throughput workloads.
Set up clear monitoring and alerting for model performance (e.g. Prometheus, Grafana, CloudWatch).
Design secure, reliable infrastructure on AWS (S3, EC2, SageMaker) using Infrastructure-as-Code tools like Terraform.

Platform Acceleration:

Be embedded in other teams, from Generations to Enterprise, to support high-impact projects requiring deep ML expertise.
Develop shared tooling, reusable workflows, and architecture patterns that help teams across Leonardo build and ship faster.
Promote knowledge-sharing, best practices, and scalable solutions across the organisation.

Skills We Love:

Generative AI Experience: Experience deploying diffusion-based or similar generative models into production and working with inference optimisation techniques.
MLOps Expertise: Skilled in building automated, reliable workflows for training, deploying, and monitoring ML models at scale.
Infrastructure & Cloud: Hands-on with AWS (S3, EC2, SageMaker), Kubernetes, Docker, and Infrastructure-as-Code (Terraform).
Performance & Efficiency: Proficient in techniques such as quantisation, distillation, caching, and distributed inference.
Data Foundations: Ability to design scalable data pipelines and storage solutions (SQL/NoSQL).
Engineering Craft: Strong Python skills and a focus on writing clear, maintainable, and collaborative code.
Collaboration & Growth: Thrive in cross-functional teams, value open feedback, and enjoy supporting others’ success while learning continuously.

Our Culture:

Inclusive Culture: We celebrate diversity and are committed to creating an inclusive environment where everyone feels valued and empowered. At Leonardo AI, your unique perspectives and experiences are welcomed and essential to our success.
Flexible Work Environment: We understand the importance of work-life balance. Enjoy the flexibility to work remotely or from our vibrant offices. We have employees all over Australia, ensuring you can thrive personally and professionally.
Empowering Growth: Your development is our priority. We offer continuous learning opportunities and career growth tailored to your goals. You’ll be encouraged to grow and excel in your career at Leonardo AI.
Impactful Work: Join us in shaping the future of AI. You'll work on innovative projects that have a meaningful impact, and your contributions will help drive advancements in AI creativity.

Leonardo.Ai Benefits:

A range of benefits to set you up for every success in and outside of work. Here's a taste of what's on offer:
Impact the future of AI
Reward package including equity - we want our success to be yours too
Inclusive parental leave policy that supports all parents & carers with 18 weeks paid leave
An annual Vibe & Thrive allowance to support your wellbeing, social connection, office setup & more
Flexible leave options that empower you to be a force for good, take time to recharge and support you personally, including remote working abroad
Support with your professional development
Fun and engaging company events, both virtual and in-person
20 days annual leave

Please apply…

","hiringOrganization":{"@type":"Organization","name":"Leonardo.Ai","sameAs":"https://leonardo.ai/"},"jobLocation":{"@type":"Place","address":{"@type":"PostalAddress","addressLocality":"Sydney (Hybrid)","addressCountry":"Australia","addressRegion":"Asia/Pacific"}}}},{"@type":"ListItem","position":32,"item":{"@type":"JobPosting","title":"Senior Machine Learning Engineer","datePosted":"2025-08-03","description":"

Blackpoint Cyber is the leading provider of world-class cybersecurity threat hunting, detection and remediation technology. Founded by former National Security Agency (NSA) cyber operations experts who applied their learnings to bring national security-grade technology solutions to commercial customers around the world, Blackpoint Cyber is in hyper-growth mode, fueled by a recent $190m series C round.

What You’ll Do

Blackpoint Cyber is a provider of leading-edge cybersecurity threat hunting, detection, and response technology. Blackpoint was founded by former National Security Agency (NSA) cyber operations experts that applied their expertise to bring nation/state grade technologies to commercial customers around the world. We are looking for an experienced ML Engineer who will operate in a technical lead role for the machine learning function of our A.I. business unit. Candidates will directly support Blackpoint’s cyber security mission, helping to stop cyber-attacks, and protecting Blackpoint’s rapidly growing customer base.

Summary:

As ML Engineer, you will be responsible for building out Blackpoint Cyber’s machine learning solutions to support development of our A.I. products and features. You will report directly to the Head of Artificial Intelligence.

Who You Are:

Blackpoint Cyber is looking for someone who has:

• 5+ years of experience in hands-on ML Engineering, with a track record of delivering A.I. products and services into production.

• Experience building in the well-architected mindset—for efficiency, performance, security, and reliability.

• Strong analytical and problem-solving abilities, with a focus on data-driven decision-making.

• Excellent communication and interpersonal skills, with the ability to influence and collaborate with stakeholders at all levels.

What You’ll Bring:

Experienced in:

• Cloud-based ML Infrastructure (AWS)

• Model Development & Deployment OperaJons (SageMaker, Airflow)

• Inference Streams & Event-driven Processing (KaZa, Spark)

• MLOps Workflows (Airflow, MLFlow, KubeFlow)

• Pipeline AutomaJon (A.I. CI/CD, Infrastructure as Code)

• ML Governance (Data, Model, & Feature Versioning, Monitoring & TesJng)

• Containerized Services (Docker, Kubernetes)

• Scripting Language (Python, Bash)

• Query Language (SQL, Ksql)

• GitFlow & DevOps Best Practices

Nice to Have:

• Transformer Neural Nets

• Agile Scrum

• Programming (Scala, Java)

• Experience in Cybersecurity, IoT, or NLP fields

How You’ll Make an Impact:

• Develop, optimize, and deploy ML models.

• Design, build, and administrate model building and serving infrastructure.

• Implement ML workflows as containerized Infrastructure as Code.

• Build & automate standardized container pipelines for training, feature engineering, and inference channels.

• Conduct performance, load, and deployment testing of delivered ML solutions.

• Develop ML governance utilities for oversight and administration of deployed infrastructure.

• Implement data, feature, and model lifecycle best practices.

• Contribute to A.I. architecture and design decisions.

• Collaborate closely with cross-functional teams, including Engineering, Blackpoint Cyber’s Security OperaJons Center (SOC), and our Adversary Pursuit Group (APG)

Blackpoint Cyber welcomes and encourages applications from qualified individuals of all races, colors, religions, sex, sexual orientation, gender identity or expression, national origin, age, marital status, or any other legally protected status. We are committed to equality of opportunity in all aspects of employment. For eligible employees in the US, Blackpoint offers competitive Health, Vision, Dental, and Life Insurance plans, a robust 401k plan, Discretionary Time Off, and other minor perks.

","hiringOrganization":{"@type":"Organization","name":"Blackpoint Cyber","sameAs":"https://blackpointcyber.com/"},"jobLocation":{"@type":"Place","address":{"@type":"PostalAddress","addressLocality":"Remote - Canada","addressCountry":"Canada","addressRegion":"North America"}}}},{"@type":"ListItem","position":33,"item":{"@type":"JobPosting","title":"Senior Machine Learning Engineer","datePosted":"2025-08-03","description":"Company Description
Govini transforms Defense Acquisition from an outdated manual process to a software-driven strategic advantage for the United States. Our flagship product, Ark, supports Supply Chain, Science and Technology, Production, Sustainment, and Modernization teams with AI-enabled Applications and best-in-class data to more rapidly imagine, develop, and field the capabilities we need. Today, the national security community and every branch of the military rely on Govini to enable faster and more informed Acquisition decisions.
Job Description
We are seeking a Natural Language Processing expert to join our team and help us build cutting-edge machine learning technology that will replace complex, time-consuming, manual processes with automation and intelligence that helps Govini end-users make scientific and analytical decisions. We're looking for world-class talent to join our team where you will have the opportunity to help develop a wide range of solutions that transform natural language data into useful features for classification algorithms, as well as implement the latest technology to improve user search functionality.
In order to do this job well, you must be a curious and eager problem solver with a hunger for building well-designed models and solving problems in an ambiguous space. You share our intolerance of mediocrity. You’re uber-smart, challenged by figuring things out and producing simple solutions to complex problems. Knowing there are always multiple answers to a problem, you know how to engage in a constructive dialogue to find the best path forward. You’re scrappy. We like scrappy.
This role is a full-time position located out of our office in Pittsburgh, PA. This role may require up to 10% travel\n

Scope of Responsibilities

Inform and implement the design and development of NLP applications to enhance the intelligence and efficiency of our data analytics software-as-a-service platform
Review, verify, and aggregate the most appropriate annotated datasets for the best-supervised learning methods
Ability to work with taxonomy experts to create and validate dataset annotation
Use well-formed and effective text representation to change and adapt natural language documents into user-friendly features
implement the latest technology to improve user search functionality as well as integrate state of the art LLM models into our Ark.ai platform to enhance user experience.
Develop new algorithms and modeling techniques and conduct sound experiments to verify model results and integrate models into the live production system
Establish meaningful criteria for evaluating algorithm performance and suitabilityImplement working, scalable, production-ready models and code
Keep up to date with Machine Learning best practices and evolving open-source frameworks
Regularly seek out innovation and continuous improvement, finding efficiency in all assigned tasks
Collaborate closely with fellow taxonomists, software engineers, data scientists, data engineers, and QA engineers

Qualifications

US Citizenship is Required

Required Skills:

Advanced degree, or bachelor’s with at least 3 years of experience, in Data Science, Machine Learning or a related field
Minimum 3 years experience with hands-on development of NLP models
In-depth understanding of NLP methods for text representation, semantic extraction techniques, data structures, and modeling
Practical experience in building, developing, and productionizing both supervised and unsupervised machine learning models
Advanced software skills in Python
Advanced ability in forming SQL queries
A strong desire to learn, investigate, and implement cutting-edge technologies
Ability to work collaboratively throughout the design process.

Desired Skills:

Current possession of a U.S. security clearance, or the ability to obtain one with our sponsorship
Experience in or exposure to the nuances of a startup or other entrepreneurial environment
Experience in deploying ML models in Kubernetes environments
Experience developing custom training sets for large language models
Experience productionizing transformer-based models

We firmly believe that past performance is the best indicator of future performance. If you thrive while building solutions to complex problems, are a self-starter, and are passionate about making an impact in global security, we’re eager to hear from you.
Govini is an Equal Opportunity Employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, national origin, sexual orientation, gender identity, disability and protected veterans status or any other characteristic protected by law.","hiringOrganization":{"@type":"Organization","name":"Govini","sameAs":"https://govini.com/"},"jobLocation":{"@type":"Place","address":{"@type":"PostalAddress","addressLocality":"Pittsburgh, PA","addressCountry":"United States","addressRegion":"North America"}}}},{"@type":"ListItem","position":34,"item":{"@type":"JobPosting","title":"Senior Machine Learning Engineer","datePosted":"2025-08-06","description":"

Company Description

Are you ready to be a big part of something big?

At carsales, we're all about making buying and selling a great experience. For 28 years we’ve been evolving with the new economy to help people choose how they move today and tomorrow.

When it comes to your career, we want to provide big opportunities to help you make a big impact. But for this to be possible, we strive to feel small. Small enough to quickly change tact, small enough to learn from different departments and small enough to connect authentically with leadership.

With a vision to be the global leader in online vehicle marketplaces. We transform how people buy and sell across the globe. We discover new ideas and make them happen. We continue to grow, and we continue to evolve – and we aren’t afraid to make big bets.

When it comes to your career, we want to provide big opportunities to help you make a big impact. But for this to be possible, we strive to feel small. Small enough to quickly change tack, small enough to learn from different departments and small enough to connect authentically with leadership.

A career in Machine Learning will see you working on products that are used every single day by our millions of customers all over the world.

Not something you’d expect from one of the country’s biggest tech companies, is it?

What’s on offer:

A place where you can move your career forward, where you’ll be continuously backed to make new ideas happen, and the chance to do work that makes real, significant impact in the world.
We’re proud to be recognised as one of Australia’s Best Workplaces™ by Great Place to Work®, a Family Friendly Workplace, a WORK180 endorsed employer for women.
The support of a highly engaged, high-performing team including a leadership team that’s you’ll actually have face time with.
24 weeks paid parental leave for primary caregivers, four weeks paid secondary caregivers leave, six weeks paid gender affirming care leave.

Job Description

What you’ll do:

We’re seeking a skilled and motivated Machine Learning Software Engineer with strong experience in AWS Cloud technologies. This role offers the opportunity to work on cutting-edge AI solutions, collaborating with a diverse team to deliver impactful outcomes across our platforms.

What You’ll Be Doing

Architecting and designing scalable software systems on AWS Cloud, contributing to both high-level strategy and hands-on implementation.
Building, deploying, and maintaining AI models and training pipelines, ensuring performance, reliability, and alignment with business goals.
Creating comprehensive design documentation, including both high-level and low-level specifications, and translating these into clean, maintainable code.
Collaborating cross-functionally with data scientists, product managers, and fellow engineers to develop elegant, efficient solutions, while engaging a variety of stakeholder throughout the process.
Leveraging AWS services such as Bedrock, SageMaker, S3, DynamoDB, RDS, Lambda, ECS, and Terraform. Experience with Batch, Step Functions, and API Gateway is highly regarded.

Qualifications

What are we looking for?

Demonstrated expertise in Python, containerization (Docker), and the AWS ecosystem, with hands-on experience supporting high-traffic environments focused on scalability, reliability, and performance.
Strong understanding of professional software engineering practices, including the full software development lifecycle: coding standards, code reviews, CI/CD pipelines, source control, build processes, testing, and operational support.
Proficiency with AWS services such as Bedrock, SageMaker, S3, DynamoDB, RDS, Lambda, ECS, and Terraform. Familiarity with Batch, Step Functions, and API Gateway is highly regarded.
Proven ability to translate business questions into data-driven solutions, using quantitative techniques and available data to deliver meaningful outcomes.
Familiarity with common machine learning techniques (e.g., regression, decision trees, clustering, embeddings, image classification, object detection), and practical experience applying them to real-world problems.
Inclusive and collaborative mindset, aligned with our core behaviours: we change the game, we own it, we step in, we are curious, and we don’t take ourselves too seriously.
Experience or interest in Generative AI technologies, such as prompt engineering, vector databases, hybrid search, function calling, and evaluation pipelines. Bonus points for experience deploying AI/ML models using frameworks like TensorFlow, PyTorch, SKLearn, or MLOps tools such as Metaflow, Kubeflow, or MLflow.

Additional Information

A few other things we want to let you know about...

carsales is an equal opportunity employer and we pride ourselves on fostering a diverse and inclusive workplace. We encourage everyone of all ages, genders and backgrounds to apply. If you’re a candidate with a disability or you’ll need some adjustments to be at your best, let us know how we can provide you with additional support.
We know how important keeping that balance between work/life is and have a range of flexible working options on offer, including part time work. We are open to this conversation during our recruitment process - if you want to know more just ask.
We are a proud Circle Back Initiative Employer which means we are committed to responding to every job applicant.
Successful candidates joining the carsales family are required to undergo a National Police Record check and must have full-time Australian working rights on an ongoing basis.

So come and join our team - because every role is a big role in our plans to go big.

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We are building a planet-scale multi-modal database from the ground up. You will be part of the team that is reimagining the databases in the era of Large Language Models (LLMs) by deeply integrating Artificial Intelligence (AI) into all parts of the stack.

As a Senior Machine Learning Engineer, you will collaborate with a team of passionate engineers, driving ideas to impactful results in a fast-paced environment. You will work on designing, building, and deploying large-scale machine learning systems, with an emphasis on production-grade solutions involving data pipelines, distributed training, model serving, and performance optimization. You are experienced in machine learning engineering from ideation and algorithm selection, to architecture and implementation, to deployment and continuous improvement.

Successful engineers in our team have problem solving, design, coding and debugging skills, drive for execution and results, rigor in delivering quality software and a desire for continuous learning. Our team values a friendly, collaborative atmosphere with a passion for technology, and we believe that a diverse team with diverse perspectives that applies empathy and uses great communication skills helps deliver superior products and is key to success. This is a great opportunity to challenge yourself, grow your career, and influence the next generation of computing at Microsoft.

Microsoft’s mission is to empower every person and every organization on the planet to achieve more. As employees we come together with a growth mindset, innovate to empower others, and collaborate to realize our shared goals. Each day we build on our values of respect, integrity, and accountability to create a culture of inclusion where everyone can thrive at work and beyond.

In alignment with our Microsoft values, we are committed to cultivating an inclusive work environment for all employees to positively impact our culture every day.

Responsibilities

Develop and deploy scalable Machine Learning models.
Develop robust evaluation frameworks to assess model performance, conduct systematic benchmarking, and address identified weaknesses while ensuring compliance with customer standards.
Defines the vision and strategy for collaboration efforts between researchers and development teams at the individual product level. Brings new technology and approaches into production by applying long-term research efforts to solve immediate product needs. Drives high-stakes negotiations across teams to ensure cutting edge technology is being applied to products in a practical way that meets key business objectives. Ensures that teams apply an understanding of research approaches used across and outside of the company to leverage (and not re-invent) solutions. Represents the organization across the company.
Incorporates key business and product requirements to define a clear agenda and vision that influences the direction of the company/products and provides a competitive or strategic advantage. Drives programs structured around the specificity of key business challenges. Provides strategic direction for the kinds of data used to solve problems.
Embody our culture and values.

Qualifications

Required Qualifications

Bachelor's Degree in Computer Science, Machine Learning or Artificial Intelligence, or related field AND 4+ years related experience (e.g., statistics, predictive analytics, research)
- OR Master's Degree in Computer Science, Machine Learning or Artificial Intelligence, or related field AND 2+ years related experience (e.g., statistics, predictive analytics, research)
- OR Doctorate in Computer Science, Machine Learning or Artificial Intelligence, or related field AND 2+ years related experience (e.g., statistics, predictive analytics, research)
- OR equivalent experience.
Proven experience in training large-scale modern Machine Learning (ML) models (e.g., transformers, diffusion models, foundation models).
Hands-on experience in key model optimization techniques (e.g., mixed precision training, distributed training, fine-tuning, RLHF, LoRA).
Familiarity with model evaluation, data curation pipelines, and reproducible research practices.

Preferred Qualifications

Master's Degree in Computer Science, Machine Learning or Artificial Intelligence, or related field AND 4+ years related experience (e.g., statistics, predictive analytics, research) 
- OR Doctorate in Computer Science, Machine Learning or Artificial Intelligence, or related field AND 3+ years related experience (e.g., statistics, predictive analytics, research) 
- OR equivalent experience. 
Deep understanding of modern deep learning frameworks such as PyTorch or TensorFlow, and scalable training infrastructure.
First-author publication in top-tier machine learning conferences or journals (e.g., NeurIPS, ICML, ICLR, CVPR, ACL).

Microsoft is an equal opportunity employer. All qualified applicants will receive consideration for employment without regard to age, ancestry, color, family or medical care leave, gender identity or expression, genetic information, marital status, medical condition, national origin, physical or mental disability, political affiliation, protected veteran status, race, religion, sex (including pregnancy), sexual orientation, or any other characteristic protected by applicable laws, regulations and ordinances. If you need assistance and/or a reasonable accommodation due to a disability during the application or the recruiting process, please send a request via the Accommodation request form.

Benefits/perks listed below may vary depending on the nature of your employment with Microsoft and the country where you work.

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Job Description

Purpose of the role

To build and maintain the systems that collect, store, process, and analyse data, such as data pipelines, data warehouses and data lakes to ensure that all data is accurate, accessible, and secure.

Accountabilities

Build and maintenance of data architectures pipelines that enable the transfer and processing of durable, complete and consistent data.
Design and implementation of data warehoused and data lakes that manage the appropriate data volumes and velocity and adhere to the required security measures.
Development of processing and analysis algorithms fit for the intended data complexity and volumes.
Collaboration with data scientist to build and deploy machine learning models.

Vice President Expectations

Contribute or set strategy, drive requirements and make recommendations for change. Plan resources, budgets, and policies; manage and maintain policies/processes; deliver continuous improvements and escalate breaches of policies/procedures.
Be a subject matter expert within own discipline and will guide technical direction. Lead collaborative, multi-year assignments and guide team members through structured assignments, identify the need for the inclusion of other areas of specialisation to complete assignments. Train, guide and coach less experienced specialists and provide information affecting long term profits, organisational risks and strategic decisions.
Advise key stakeholders, including functional leadership teams and senior management on functional and cross functional areas of impact and alignment.
Manage and mitigate risks through assessment, in support of the control and governance agenda.
Demonstrate leadership and accountability for managing risk and strengthening controls in relation to the work your team does.
Demonstrate comprehensive understanding of the organisation functions to contribute to achieving the goals of the business.
Collaborate with other areas of work, for business aligned support areas to keep up to speed with business activity and the business strategies.
Create solutions based on sophisticated analytical thought comparing and selecting complex alternatives. In-depth analysis with interpretative thinking will be required to define problems and develop innovative solutions.
Adopt and include the outcomes of extensive research in problem solving processes.
Seek out, build and maintain trusting relationships and partnerships with internal and external stakeholders in order to accomplish key business objectives, using influencing and negotiating skills to achieve outcomes.

All colleagues will be expected to demonstrate the Barclays Values of Respect, Integrity, Service, Excellence and Stewardship – our moral compass, helping us do what we believe is right. They will also be expected to demonstrate the Barclays Mindset – to Empower, Challenge and Drive – the operating manual for how we behave.

Join our innovative AI/ML team at Barclays Corporate Bank as a Senior Machine Learning Engineer, where we bridge the gap between cutting-edge data science exploration and real-world business application integration. We manage internal cloud platforms that support exploratory data science work while specialising in transforming conceptual ML models into production-ready applications that drive critical business decisions and processes. As part of Barclays' strategic AI/ML initiative, our team plays a vital role in establishing the corporate bank as a leader in financial data analytics innovation. We offer the opportunity to work with enterprise-scale data using cloud technologies, implement MLOps best practices, and collaborate with talented data scientists to deliver solutions that create measurable business impact across the organization.

To be successful in this role, you will need the following:

Strong proficiency and experience in AWS based Machine Learning technologies (AWS SageMaker, Lambda, S3, EC2).
Experience with CI/CD pipelines and Docker containerisation for ML model development/deployment.
Data preprocessing and feature engineering expertise.
Programming skills in Python and ML frameworks (TensorFlow, Torch, scikit-learn).
Statistical analysis and model evaluation capabilities.
Previous experience in the banking sector is mandatory.

Some other highly valued skills may include:

Experience with experiment tracking and model registry tools (MLflow, DVC).
Knowledge of infrastructure as code (Terraform, CloudFormation).
Familiarity with data visualisation tools and techniques.
Advanced knowledge of ML algorithms and their optimisation.
Experience with distributed computing for large-scale ML workloads (Spark).
Experience with pricing models or pricing-related projects is strongly preferred.
Additional Experience in GenAI projects implementation (multiple RAG patterns, prompt management, agentic workflows) is preferred.

You may be assessed on the key critical skills relevant for success in role, such as risk and controls, change and transformation, business acumen, strategic thinking and digital and technology, as well as job-specific technical skills.

The successful candidate will be based in Glasgow.

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Company Description

We’re ASOS, the online retailer for fashion lovers all around the world.

We exist to give our customers the confidence to be whoever they want to be, and that goes for our people too. At ASOS, you’re free to be your true self without judgement, and channel your creativity into a platform used by millions.

But how are we showing up? We’re proud members of Inclusive Companies, are Disability Confident Committed and have signed the Business in the Community Race at Work Charter and we placed 8th in the Inclusive Top 50 Companies Employer list.

Everyone needs some help showing up as their best self. Let our Talent team know if you need any adjustments throughout the process in whatever way works best for you.

Job Description

We are looking for a Senior Machine Learning Engineer, with expertise in deep learning, to join our cross-functional AI Style Discovery team.

In role, you will a senior IC who will be productionising machine learning systems across that help our customers discover and shop complete outfits that resonate with both their personal style and current fashion trends. Our mission is to elevate the fashion experience and ship with high scale ML capabilities.

What you’ll be doing:

You will be part of an agile, cross-functional team building and improving our causal algorithms for the pricing and customer targeting space.
You will be working alongside scientists in driving the implementation and deployment of at-scale solutions for our hundreds of millions of customers/products, creating measurable impact across the business.
You will be deploying batch and online machine learning models at high scale.
You will be continually developing and improving our code and technology, taking an active role in the conception of brand-new features.
You will be mentoring and coaching junior members of the team, supporting their technical progress.
You will contribute to the team's technical direction, establish ML standards, and drive quality across ASOS's ML community, while sharing expertise gained from the team.

We believe being together in person helps us move faster, connect more deeply, and achieve more as a team. That’s why our approach to working together includes spending at least 2 days a week in the office. It’s a rhythm that speeds up decision-making, helps ASOSers learn from each other more quickly, and builds the kind of culture where people can grow, create, and succeed.

Qualifications

About You

You have professional experience in machine learning with expertise in deep learning methods and their practical applications in production environments.
You possess mastery of deep learning frameworks and distributed computing frameworks for implementing large-scale deep learning models.
You have proven ability to create and manage multi-instance clusters for distributed and parallel training across GPUs, demonstrating proficiency in data and model parallelism techniques.
You have strong understanding of software development lifecycles and engineering practices (Data pipelines, CI/CD, containerisation, observability) - specifically ML Ops principles, techniques and tooling.
You’re comfortable providing technical leadership, mentoring, and coaching to more 1-2 junior engineers. You will contribute to wider engineering initiatives across ASOS.

Additional Information

BeneFITS’

Employee discount (hello ASOS discount!)
ASOS Develops (personal development opportunities across the business)
Employee sample sales
Access to a huge range of LinkedIn learning materials
25 days paid annual leave + an extra celebration day for a special moment
Discretionary bonus scheme
Private medical care scheme
Flexible benefits allowance - which you can choose to take as extra cash, or use towards other benefits

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What you'll Accomplish:

Research, prototype, and develop AI-driven models for robotic manipulation, grasping, and object interaction.
Design and optimize Classical ML / deep learning and reinforcement learning (RL) models for robotic control and decision-making.
Develop simulation-driven ML pipelines, integrating synthetic data, real-world sensor data, and reinforcement learning.
Work with different learning models, including Large Language Models (LLMs), transformer-based architectures, and generative AI to enhance robotic intelligence.
Collaborate with robotics engineers, software developers, and mechatronics teams to integrate ML models into real-world robotic systems.
Design and implement scalable ML frameworks for real-time robotics applications.
Conduct model evaluation, benchmarking, and performance tuning to improve accuracy, robustness, and generalization.
Develop and maintain data pipelines, including sensor data collection, annotation, and preprocessing for AI model training.
Experiment with foundation models and generative AI for robotics applications.
Work with physics-based simulators (Isaac Sim, Mujoco, PyBullet, Gazebo, DRAKE) to train and validate ML models.

Who you are:

5+ years of experience in machine learning, deep learning, or reinforcement learning for robotics.
Hands-on experience with robotic perception, motion control, and adaptive decision-making models.
Strong background in ML model development, training pipelines, and real-world deployment.
Experience in R&D environments, rapidly prototyping and iterating on AI models.
Familiarity with robotics simulation environments and synthetic data generation.
Strong understanding of multi-modal sensor fusion (LiDAR, depth cameras, IMUs) and time-series modeling.
Experience working with different AI models, including LLMs, generative AI, diffusion models, and reinforcement learning algorithms.
Programming: Proficiency in Python, C++, and experience with robotics frameworks (ROS2, PyTorch, TensorFlow, JAX, OpenCV).ML Techniques: Deep learning (CNNs, Transformers), reinforcement learning (PPO, SAC, DDPG), and self-supervised learning.
Simulation & Modeling: Experience with physics-based simulation tools (Isaac Sim, Mujoco, Gazebo, PyBullet).Data Processing: Expertise in large-scale dataset curation, sensor fusion, and distributed ML pipelines.
Optimization & Deployment: GPU acceleration, CUDA, TensorRT, and real-time model optimization.
Experience with edge AI and deploying ML models on embedded robotics platforms.
Background in multi-agent reinforcement learning (MARL) for robotic coordination.
Understanding of generative AI (Diffusion Models, Transformers) applied to robotic environments.
Experience with foundation models and fine-tuning large-scale pretrained ML models for robotics.
Passionate about AI for robotics and solving hard, real-world problems.
Strong R&D mindset, excited about prototyping and pushing AI innovation.
Self-driven, curious, and thrives in an experimental, fast-paced environment.
Effective collaborator, able to work cross-functionally with robotics and software teams.
Willing to work onsite at our Cambridge,MA office atleast 3 days a week

About Pickle RobotPickle Robot is a pioneer in Physical AI for supply chain applications. Today Pickle robots autonomously unload trucks, trailers, and import containers at human-scale or better performance. The alternative is manual work that is difficult, dirty, sometimes dangerous, and increasingly hard to staff at distribution centers around the globe. Pickle Robot is laser focused on automating truck unloading using generative AI, machine learning, computer vision, advanced sensors, and industrial robotics to deliver engineered products customers rely on. Pickle Robot Unload Systems work alongside people on loading docks to make the work safer, faster, and more efficient. Pickle robots are physical AI that unload trucks.
Pickle provides best-in-class benefits including health, dental, & vision insurance; unlimited vacation, along with all federal and state holidays; 401K contributions of 5% your salary, travel supplies, and other items to make your working life more fun, comfortable, and productive.","hiringOrganization":{"@type":"Organization","name":"Pickle Robot","sameAs":"https://picklerobot.com/"},"jobLocation":{"@type":"Place","address":{"@type":"PostalAddress","addressLocality":"Cambridge, MA","addressCountry":"United States","addressRegion":"North America"}}}},{"@type":"ListItem","position":39,"item":{"@type":"JobPosting","title":"Senior Machine Learning Engineer","datePosted":"2025-08-11","description":"

About us:

VideaHealth is a cutting-edge AI-powered solution for dentistry, developed by a team of seasoned leaders, engineers, AI scientists, and clinicians spun out of MIT. Our vision is to be the first company to diagnose a billion people globally. Our product is already used by thousands of dental clinicians to improve the quality of care through faster diagnoses, increase operating efficiencies, and improved patient understanding.

About the position:

We are looking for a Senior Machine Learning Engineer to join our growing ML team. This is an exciting opportunity to contribute and grow your technical skills by building end to end highly impactful software medical devices that will ultimately impact the lives of millions of people.

In this role, you’ll take full ownership of high-impact projects and design robust infrastructure that powers our clinical applications, from computer vision models to decision support systems. You’ll work side-by-side with our leadership team and collaborate across a dynamic, tight-knit team that thrives on innovation and execution. You’ll have the opportunity to work at the cutting edge of AI and healthcare, in close collaboration with renowned advisors from MIT and Harvard, and alongside researchers, physicians, and regulatory experts, including those with deep FDA experience.

We’re looking for a hands-on ML expert who’s excited to build, ship, and own real-world products. If you're a builder with a passion for impact, eager to grow fast and help define the future of AI in healthcare — we’d love to meet you.

Key Responsibilities:

Own the design and implementation of infrastructure for reliable and highly performant deep learning and analytics pipelines with the main focus on the detection and classification of dental conditions from images.
Research, prototype, and deploy production-grade computer vision models (e.g., CNNs, transformers)
Play a critical role in defining and executing processes for managing large amounts of data, defining data sampling approaches and performance evaluations.
Write traceable, testable, and reproducible code to support FDA/CE-cleared ML workflows. Collaborate on documentation for 510(k) submissions.
Design model monitoring tools for drift detection, explainability, and performance in production.
Partner with clinical experts and software engineers to ensure models are safe, effective, and usable in real-world healthcare environments.

Requirements

Minimum of 4 years of hands-on development building deep learning models
Experience with at least one deep learning framework (e.g. PyTorch, TF, Keras)
Strong software development skills including testing (Python) and leading development in a shared codebase
Strong communication and collaboration skills

Preferred

M.S. or PhD in Computer Science or related field.

Experience in reading & implementing technical research papers
Proven track-record of high quality software development (e.g. on GitHub)
Experience in working with medical images or related Computer Vision problems
Experience in Data Analysis (e.g. statistics, performance metrics)
Experience working with cloud based platforms / providers (e.g. AWS)
Leadership/Mentorship experience

What We Offer

Fast paced and collaborative work culture in which you can gain experience, grow your technical skills and work on a wide variety of challenges over your time with us
Competitive pay, equity and benefits (flexible PTO)
Agile organization where being senior translates to being a mentor and role model for others. We lead by example.
Technical challenges on the leading edge of innovation where software and machine learning intersect.

VideaHealth is supported by some of the best investors in the world, having raised over $67M in Venture Capital from Tier 1 investors such as Spark Capital (Twitter, SnapChat, SmileDirectClub), Zetta Venture (Kaggle), and Pillar VC (PillPack), as well as angel investors such as Frederic Kerrest (Co-founder of Okta). Our work has been featured in TechCrunch, Wall Street Journal, and many other outlets.

If you want to join a breakthrough healthtech company and help accelerate its impact and growth, we encourage you to apply for this exciting opportunity!

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Company Description

Accesa is a leading technology company headquartered in Cluj-Napoca, with offices in Oradea and 20 years of experience in turning business challenges into opportunities and growth.

A value-driven organisation, it has established itself as a partner of choice for major brands in Retail, Manufacturing, Finance, and Banking. It covers the complete digital evolution journey of its customers, from ideation and requirements setup to software development and managed services solutions.

With more than 1,200 IT professionals, Accesa also has a fast-growing footprint, establishing itself as an employer of choice for IT professionals who are passionate about problem-solving through technology. Coming together in strong tech teams with a customer-centric approach, they enable businesses to grow, delivering value for our clients, partners, industry, and community.

Job Description

We are seeking a highly motivated and technically skilled Senior Machine Learning Engineer with a strong focus on Prompt Engineering, Large Language Model (LLM) Evaluation, and Python-based development. This role is central to the enhancement and evaluation of our custom GPT-based systems, contributing directly to innovation in AI-powered solutions.

Responsibilities

Prompt Engineering & Enhancement → Design, extend, and customize system prompts (e.g., chat history, instructions, rules), evaluate the impact of prompt changes, and continuously improve GPT usage scenarios while analyzing the risk-benefit of each modification.
Experimental Feature Development → Conceptualize, prototype, and validate new GPT-based features (e.g., internet search integration, prompt behavior control) to extend system capabilities.
Model Evaluation & Tracking → Evaluate new GPT/LLM releases (e.g., OpenAI models), monitor response quality and consistency, and assess upgrade relevance for various user tiers.
Knowledge Sharing & Research → Stay up to date with the latest techniques in reasoning, chaining, and context optimization, and prepare detailed evaluation reports for the Data Science team.
Python Development & Prototyping → Develop both prototype and production-level code to support AI features, ensuring reliability and maintainability aligned with product requirements.
LLM Integration & Optimization → Utilize frameworks like Langchain to build solutions, implement advanced chatbot capabilities, and contribute to experimental extensions such as tool integration or dynamic content fetching.

Qualifications

Requirements:

4+ years of experience with Python and its data science ecosystem (Pandas, NumPy, Scikit-learn), fundamental for data manipulation and modeling
Proven experience in prompt engineering and LLM behavior analysis.
Familiarity with LLM integration frameworks such as Langchain or similar.
Experience in data curation, preprocessing and tokenization for LLM training
Deep understanding of GPT-based systems and their customization potential.
Ability to translate product requirements into reliable, maintainable code.
Experience with experimental feature development and technical feasibility evaluation.
Excellent documentation and communication skills for sharing findings within a collaborative team.

Nice to have:

Experience with distributed training
Experience with MLOps for LLMs

Additional Information

At Accesa you can:

Enjoy our holistic benefits program that covers the four pillars that we believe come together to support our wellbeing, covering social, physical, emotional wellbeing, as well as work-life fusion.

Physical Wellbeing: Our wellbeing program includes medical benefits, gym support, and personalised fitness options for an active lifestyle, complemented by team events and the Healthy Habits Club.
Work-Life Fusion: In very dynamic industries such as IT, the line between our professional and personal lives can quickly become blurred. Having a one-size-fits-one approach gives us the flexibility to define the work-life dynamic that works for us.
Emotional Wellbeing: We believe that to maintain our overall health, we need to invest in our mental wellbeing just as much as we do in our physical health, social connections or in achieving work-life balance.
Social Wellbeing: As a growing community in a hybrid environment, we want to ensure we remain connected not just by the great work we do every day but through our passions and interests.

","hiringOrganization":{"@type":"Organization","name":"Accesa & RaRo","sameAs":"https://accesa.eu"},"jobLocation":{"@type":"Place","address":{"@type":"PostalAddress","addressLocality":"Employees can work remotely, Romania","addressCountry":"Romania","addressRegion":"Europe"}}}},{"@type":"ListItem","position":41,"item":{"@type":"JobPosting","title":"Senior Machine Learning Engineer","datePosted":"2025-08-10","description":"

Who we are

The Stensul Marketing Creation Platform™ reduces marketing asset creation time by up to 90% to help teams focus on improving campaign performance. With Stensul, teams launch campaigns faster by streamlining the collaboration process and simplifying creation for all marketers so they can create marketing assets that drive results. Stensul integrates with all leading ESPs/MAPs, including Marketo, Oracle Eloqua, Adobe Campaign, and Salesforce Marketing Cloud, as well as project management platforms, image libraries, live content, link tracking, and messaging platforms. Top brands that trust Stensul to solve their most demanding email problems include AAA, Demandbase, Equifax, Flywire, Greenhouse, Morgan Stanley, and Yahoo. Stensul was named Deloitte Fast 500 three years in a row and backed by top-tier venture capital firms.

What you'll do

As a Senior Machine Learning Engineer, you’ll be the company’s expert in building our first Generative AI and Machine Learning application. You will architect, implement, and deploy scalable ML solutions integrated with our product, while ensuring they’re efficient, cost-effective, and aligned with the needs of internal and external users. You’ll also mentor other engineers, shaping the way we do data modeling and coding, as well as collaborate with cross-functional teams to drive data practices that enhance business and product development.

We’re in a period of high growth which means we move fast, but you’ll do so alongside smart, driven individuals in a fun, collaborative environment with opportunities for growth. Learning Agile is one of our core values, which means that we are always identifying ways to make things better, and welcome new tools and languages that help us improve the way we work.

Specific responsibilities include:

Working with roughly defined requirements and using the business vision to elaborate and build effective solutions to data informed decision problems
Building the infrastructure required to enable self-serving of a data platform to be used by a variety of stakeholders with different skill sets
Build and deploy the company’s first Generative AI and Machine Learning application within the Stensul product, delivering impactful solutions that enhance product offerings and drive insights.
Following our agile methodology and contributing to its improvement
Own and lead initiatives from inception to delivery and maintenance in an autonomous way
Proactively adding positive energy to our rapidly growing company

Your skills and experience

Machine Learning Expertise: Proficient in building, training, deploying and monitoring ML models, with a focus on practical, scalable applications that drive product and business value.
GenAI Know-how: experience in building content generation applications utilizing techniques in the NLP &/or Image Generation field, having exposure to multi-modal generation is a plus.
Experience with GCP and Related Technologies: Skilled in GCP services (e.g., BigQuery, GKE, Vertex AI), and tools like Databricks, MongoDB, and MySQL.
Proficiency in Data Transformation and Modeling: Strong understanding of data modeling, data transformation, and preparing datasets for machine learning and analytics.
Knowledge of Orchestration and Automation Tools: Experience with orchestration tools such as Airflow or Prefect to automate and scale ML pipelines.
Programming Skills: Skilled in Python, Java or Scala or other commonly used in ML engineering. Exposure to SQL, PHP Laravel, Typescript & Vue are a plus.
Mentorship and Communication: Ability to mentor junior team members and clearly communicate complex ML concepts to both technical and non-technical stakeholders.
Autonomous, Resource-Conscious Development: Comfortable making cost-effective decisions across multi-cloud and data infrastructure setups.

What we offer

Competitive salary & benefits
Company laptop and phone reimbursement (if required)
Other awesome secret benefits we’ll tell you once you are on the team
Being a part of an amazing, inclusive team that lives by our shared values and is committed to building the next phase of stensul

Stensul is proud to be an Equal Opportunity Employer building a diverse and inclusive workforce.

If your experience is close (even if not a perfect fit) to what we’re looking for, please consider applying. Experience comes in many forms – skills are transferable, and passion goes a long way. We know that diversity makes for the best problem-solving and creative thinking, which is why we’re dedicated to adding new perspectives to the team and encourage everyone to apply.

","hiringOrganization":{"@type":"Organization","name":"Stensul","sameAs":"https://stensul.com/"},"jobLocation":{"@type":"Place","address":{"@type":"PostalAddress","addressLocality":"Buenos Aires","addressCountry":"Argentina","addressRegion":"South America"}}}},{"@type":"ListItem","position":42,"item":{"@type":"JobPosting","title":"Senior Machine Learning Engineer","datePosted":"2025-08-11","description":"Who We Are; What We Do; Where We’re Going
Magnet Forensics is a global leader in the development of digital investigative software that acquires, analyzes, and shares evidence from computers, smartphones, tablets, and IoT-related devices. We are continually innovating so our customers can deploy advanced and effective tools to protect their companies, communities, and countries. Serving thousands of customers globally, our solutions are playing a crucial role in modernizing digital investigations, helping investigators fight crime, protect assets, and guard national security. With employees based around the world, Magnet Forensics has been expanding our global presence. As a part of Magnet Forensics, you can expect to make a difference in the world, no matter what role you play. You’ll be supported through learning and development, not to mention an incredible team with unbelievable talent and integrity. If you think you would be the right person to join our team working towards this goal, we would love to hear from you!
Your RoleWe are looking for a Senior Machine Learning Engineer to join our AI Research team, designing, experimenting with, and optimizing cutting-edge ML models that power our digital forensics capabilities. You will lead the development of new models, training techniques, and evaluation methods that surface critical leads and insights for investigators, helping them solve cases faster and with greater confidence. As part of the Research team, you’ll work closely with Product, UX, and our Brain team to ensure our models push the boundaries of what’s possible, while remaining practical for real-world use. You’ll own complex ML projects end-to-end, including ideation and experimentation, to evaluation and handoff for integration advance, working with our team to advance the state-of-the-art in digital forensics.\n

What You Will Accomplish:

Design, implement, and evaluate state-of-the-art machine learning models. Lead experiments, define metrics, and iterate to improve performance, efficiency, and reliability;
Collect, build, and work with complex, real-world datasets, developing preprocessing, augmentation, and feature engineering techniques that enhance model training and fairness;
Collaborate cross-functionally with our Brain team to ensure models are production-ready, scalable, and meet real user needs.
Stay at the forefront of ML research, assessing new techniques, frameworks, and trends, and translating them into practical innovations for our products;
Mentor other engineers on ML best practices, experimental design, and technical decision-making;
Contribute to building reusable research infrastructure and tooling that accelerates experimentation and improves reproducibility;
Ensure ethical and responsible AI practices are integrated into model design, training, and evaluation.

Why You’ll Love This Role:

In your first 90 days, you’ll get hands-on with our Research team, experimenting with real-world datasets and evaluation pipelines to improve the accuracy, efficiency, or robustness of our models. You’ll collaborate closely with Product, UX, and Brain to ensure your work addresses investigator needs and is ready for integration into production systems. By the end of your first three months, you’ll have taken ownership of a key research initiative, delivering results that directly advance our AI capabilities and lay the groundwork for future innovations.

What We Are Looking For:

We’re looking for someone who checks off most, but not all, of the boxes listed in “skills and experiences”. It’s more important to us to find candidates who can display indicators of success through skills they have developed and experiences they have been a part of, than to find folks who have ‘been there, done that”. We want to be part of your development journey, and we’ll learn as much from you as you learn from us.

Required Skills:

5+ years of professional experience in machine learning or applied AI, with a track record of delivering models into production or production-ready pipelines;
Strong Python programming skills, with experience in building maintainable, scalable ML codebases;
Experience designing and running experiments, selecting appropriate evaluation metrics, and interpreting results to guide iteration;
Hands-on experience with deep learning frameworks (eg, PyTorch, TensorFlow) and deployment frameworks (eg, Triton, TorchServer);
Experience working with large, complex, and/or unstructured datasets;
Understanding of the trade-offs between model complexity, accuracy, training cost, and inference speed;
Ability to work cross-functionally with engineers, researchers, product managers, and designers;
Strong communication skills for both technical and non-technical audiences;
Bachelor’s or Master’s degree in Computer Science, Machine Learning, or a related technical field, or equivalent practical experience in applied ML research and engineering.

Nice to Have:

Experience with self-supervised, multimodal, or retrieval-augmented learning approaches;
Background in NLP, computer vision, or other relevant ML domains;
Familiarity with MLOps tooling (eg, experiment tracking, model versioning, CI/CD for ML);
Experience mentoring engineers or leading ML research initiatives;
Contributions to open-source ML projects or publications in peer-reviewed venues;
Experience working with cloud providers like AWS or Azure is an asset.

The Most Important Thing:

We’re looking for candidates that can provide examples of how they have demonstrated Magnet CODE in their previous experiences:
CARE – We care about each other and our mission to make a difference in the world.
OWN – We are accountable for our results – while never forgetting to act with integrity, empathy, and respect.
DEDICATE – We put our heart and soul into meeting the needs of our customers and helping them serve the people they protect.
EVOLVE – We are constantly innovating and exploring new ways to work together to make an impact with our work.

Compensation & Benefits

The Compensation Range is for the primary location for which the job is posted. Please note that the actual compensation may vary depending on location and job-related factors such as qualifications, experience, knowledge and skills. If you are applying for this role outside of the primary location and you are selected for an interview, the Talent Acquisition Partner can share more information with you. If the compensation structure for the role includes an incentive component (ie. most Sales roles) the range below represents total target compensation (TTC) (base salary + variable)

Compensation Range:

MIN: $111,300 - MID: $159,000 - MAX:$190,800 CAD

Magnet is proud to offer benefits such as:

Generous time off policies
Competitive compensation
Volunteer opportunities
Reward and recognition programs
Employee committees & resource groups
Healthcare and retirement benefits

Here at Magnet Forensics, we are committed to continuous learning and are focused on building a diverse and inclusive workforce. This commitment will be reflected in our hiring processes and embedded in our values and how we treat one another. If you’re interested in this role, but do not meet all of the qualifications listed above, we encourage you to apply anyways. Magnet Forensics is an Equal Opportunity Employer and considers applicants for employment without regard to race, colour, religion, sex, orientation, national origin, age, disability, genetics or any other basis forbidden under federal, provincial, or local law. We are committed to providing an inclusive, accessible recruitment process and work environment. Accommodation is available to all applicants upon request throughout the hiring process. Please contact aoda@magnetforensics.com should you require any accommodations.
All offers of employment at Magnet are contingent upon satisfactory completion of a background check. All background checks will be conducted in accordance with all applicable laws. Magnet will consider each position’s job duties, among other factors, in determining what constitutes satisfactory completion of the background check. Refusal to consent to a background check may be grounds for revoking an offer of employment.
US Applicants: Magnet Forensics participates in E-Verify and will provide the federal government with your Form I-9 information to confirm that you are authorized to work in the U.S.","hiringOrganization":{"@type":"Organization","name":"Magnet Forensics","sameAs":"https://www.magnetforensics.com/"},"jobLocation":{"@type":"Place","address":{"@type":"PostalAddress","addressLocality":"Waterloo / Ottawa / Toronto/ Ontario","addressCountry":"Canada","addressRegion":"North America"}}}},{"@type":"ListItem","position":43,"item":{"@type":"JobPosting","title":"Senior Machine Learning Engineer","datePosted":"2025-08-11","description":"Join phData, a dynamic and innovative leader in the modern data stack. We partner with major cloud data platforms like Snowflake, AWS, Azure, GCP, Fivetran, Pinecone, Glean and dbt to deliver cutting-edge services and solutions. We're committed to helping global enterprises overcome their toughest data challenges. \n\n\n\n\n\n \n

phData is a remote-first global company with employees based in the United States, Latin America and India. We celebrate the culture of each of our team members and foster a community of technological curiosity, ownership and trust. Even though we're growing extremely fast, we maintain a casual, exciting work environment. We hire top performers and allow you the autonomy to deliver results.

6x Snowflake Partner of the Year (2020, 2021, 2022, 2023, 2024, 2025)
Fivetran, dbt, Atlation, Matillion Partner of the Year
#1 Partner in Snowflake Advanced Certifications
600+ Expert Cloud Certifications (Sigma, AWS, Azure, Dataiku, etc)
Recognized as an award-winning workplace in US, India and LATAM

Machine Learning Engineers are the Swiss army knives of machine learning. They’re ready for anything, and they bring all the tools to ensure that data science models see the light of day. They own the infrastructure and deployment plan—from making sure data science models can actually be built using customer data to deploying them into a production environment, and everything in between. They provide thought leadership by recommending the right technologies and solutions for a given use case, from the application layer to infrastructure. Machine Learning Engineers have the team leadership and coding skills (e.g. Python, Java, and Scala) to get their solutions into production — and to help ensure performance, security, scalability, and robust data integration.

What you’ll do in this role:

Design and create environments for data scientists to build models and manipulate data
Work within customer systems to extract data and place it within an analytical environment
Learn and understand customer technology environments and systems
Define the deployment approach and infrastructure for models and be responsible for ensuring that businesses can use the models we develop
Reveal the true value of data by working with data scientists to manipulate and transform data into appropriate formats in order to deploy actionable machine learning models
Partner with data scientists to ensure solution deployability—at scale, in harmony with existing business systems and pipelines, and such that the solution can be maintained throughout its life cycle
Create operational testing strategies, validate and test the model in QA, and implementation, testing, and deployment
Ensure the quality of the delivered product

Required Experience:

At least 4 years experience as a Machine Learning Engineer, Software Engineer, or Data Engineer
4-year Bachelor's degree in Computer Engineering or a related field
Experience deploying data science models in a production setting.
Expertise in Python, Scala, Java, or another modern programming language
The ability to build and operate robust data pipelines using a variety of data sources, programming languages, and toolsets
Strong working knowledge of SQL and the ability to write, debug, and optimize distributed SQL queries
Experience working with Data Science/Machine Learning software and libraries such as h2o, TensorFlow, Keras, scikit-learn, etc.
Experience with Docker, Kubernetes, or some other containerization technology
Familiarity with multiple data source systems (e.g. JMS, Kafka, RDBMS, DWH, MySQL, Oracle, SAP)
Systems-level knowledge in network/cloud architecture, operating systems (e.g., Linux), storage systems (e.g., AWS, Databricks, Cloudera)
Production experience in core data technologies (e.g. Spark, Pandas)
Development of APIs and web server applications (e.g. Flask, Django, Spring)
Complete software development lifecycle experience including design, documentation, ong analytical abilities; ability to translate business requirements and use cases into a solution, including ingestion of many data sources, ETL processing, data access, and consumption, as well as custom analytics
Excellent communication and presentation skills; previous experience working with internal or external customers

Preferred Experience

A Master’s or other advanced degree in data science or a related field
Hands-on experience with one or more ecosystem technologies (e.g., HBase, Impala, Solr, Kudu, Streamsets, NiFi, ElasticSearch, Databricks, Snowflake, AWS/Azure/GCP)
Relevant side projects (e.g. contributions to an open source technology stack)
AWS Sagemaker, MLFlow experience

Why phData? We offer:

Remote-First Work Environment
Casual, award-winning small-business work environment
Collaborative culture that prizes autonomy, creativity, and transparency
Competitive comp, excellent benefits, generous PTO plus 10 Holidays (and other cool perks)
Accelerated learning and professional development through advanced training and certifications

phData celebrates diversity and is committed to creating an inclusive environment for all employees. Our approach helps us to build a winning team that represents a variety of backgrounds, perspectives, and abilities. So, regardless of how your diversity expresses itself, you can find a home here at phData. We are proud to be an equal opportunity employer. We prohibit discrimination and harassment of any kind based on race, color, religion, national origin, sex (including pregnancy), sexual orientation, gender identity, gender expression, age, veteran status, genetic information, disability, or other applicable legally protected characteristics. If you would like to request an accommodation due to a disability, please contact us at People Operations.

","hiringOrganization":{"@type":"Organization","name":"phData","sameAs":"https://www.phdata.io/"},"jobLocation":{"@type":"Place","address":{"@type":"PostalAddress","addressLocality":"LATAM-Remote"}}}},{"@type":"ListItem","position":44,"item":{"@type":"JobPosting","title":"Senior Machine Learning Engineer","datePosted":"2025-08-12","description":"

The Labcorp Genetics team is seeking an experienced Machine Learning Engineer to join our Applied AI team. Our team has pioneered real-time API integrations for model inference, deployed solutions leveraging state-of-the-art machine learning models, and continually brings advanced AI capabilities into practice to improve patient outcomes and business operations. In this role, you will leverage your expertise in Python, machine learning infrastructure, and model development to solve complex business problems and develop production-ready ML systems that directly contribute to improving patient outcomes and advancing healthcare.

RESPONSIBILITIES

Design, build, deploy, and monitor end-to-end ML solutions—feature pipelines, training workflows, real-time inference.
Translate open-ended clinical and operational problems into clear ML approaches and success metrics.
Lead the development of cloud-native infrastructure for secure, compliant, cost-effective model serving.
Measure and improve model accuracy, latency, and reliability; integrate new research and user feedback.
Partner with product managers, data scientists, and platform engineers; mentor teammates and set technical standards.

REQUIREMENTS

10+ years of professional software or ML engineering experience (or equivalent demonstrable expertise, e.g. through advanced degree).
Proficiency across the technical stack, from infrastructure to application code, and in ML frameworks and training/deployment workflows. Technologies include: AWS, GCP, Azure, Python, FastAPI, OpenSearch, TensorFlow, PyTorch, Kubernetes, GitHub Actions, and New Relic.
Strong analytical and problem-solving skills, with a proven ability to create solutions with impact beyond your team.
Experience with data preprocessing, feature engineering, model training, and model serving at production scale.
Able to drive and deliver cross-team or cross-discipline AI development projects on time and with high quality.
Excellent written and verbal communication skills.

PREFERRED

Experience with LLMs, RAG, embeddings, vector search pipelines.
Experience with cloud platforms such as AWS, GCP, or Azure.
Familiarity with MLOps best practices and tools for model versioning and deployment (data drift detection, canary/shadow deploys).
Knowledge of genetics or experience in the healthcare domain.

EDUCATION

Advanced degree in Computer Science, Machine Learning, or a related field.

Application Window closes 9/29/2025

Pay Range: $165-205k annual salary

All job offers will be based on a candidate’s skills and prior relevant experience, applicable degrees / certifications, as well as internal equity and market data. The position is also eligible for an annual bonus under the Labcorp Bonus Plan. Bonuses are payable based on corporate and/or business segment performance and are subject to individual performance modifiers.

Benefits: Employees regularly scheduled to work 20 or more hours per week are eligible for comprehensive benefits including: Medical, Dental, Vision, Life, STD/LTD, 401(k), Paid Time Off (PTO) or Flexible Time Off (FTO), Tuition Reimbursement and Employee Stock Purchase Plan. Casual, PRN & Part Time employees regularly scheduled to work less than 20 hours are eligible to participate in the 401(k) Plan only. For more detailed information, please click here.

Labcorp is proud to be an Equal Opportunity Employer:

Labcorp strives for inclusion and belonging in the workforce and does not tolerate harassment or discrimination of any kind. We make employment decisions based on the needs of our business and the qualifications and merit of the individual. Qualified applicants will receive consideration for employment without regard to race, religion, color, national origin, sex (including pregnancy, childbirth, or related medical conditions), family or parental status, marital, civil union or domestic partnership status, sexual orientation, gender identity, gender expression, personal appearance, age, veteran status, disability, genetic information, or any other legally protected characteristic. Additionally, all qualified applicants with arrest or conviction records will be considered for employment in accordance with applicable law.

We encourage all to apply

If you are an individual with a disability who needs assistance using our online tools to search and apply for jobs, or needs an accommodation, please visit our accessibility site or contact us at Labcorp Accessibility. For more information about how we collect and store your personal data, please see our Privacy Statement.

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In a nutshell

As a Machine Learning Engineer at Picnic, you will design and deploy intelligent systems to solve our company’s biggest challenges. Beyond building models, you will productionize them with strong monitoring and seamless integration into operational systems. You will collaborate closely with stakeholders to ensure the right problems are solved and that solutions deliver real-world impact.

All using high quality data. Our data is registered, logged, and consistent, enabling you to focus on building and improving models rather than cleaning data. This role combines the skills of a consultant, software engineer, and applied mathematician.

Tricks of the trade

You will definitely:

Identify and execute improvement possibilities together with other ML Engineers and (product) analysts
Collaborate on your project from inception to production, to continuous improvement
Develop tools and enhancements for our cloud-based Machine Learning platform

You could work on various projects and fields, such as:

Demand forecasting: delivery, article, trip volumes, used Picnic-wide
Fraud detection: helping us keep troublemakers out of our store
Recommendation systems: generating useful in-app grocery suggestions
Search and ranking: helping our customers find exactly what they need
Predicting delivery drop-off times: making sure we’re on-time at every customer’s door
Vision: ensuring quality control and smooth operations within our warehouses

Check out some of our previous machine learning projects here: https://blog.picnic.nl/tagged/machine-learning

We’re looking for

Master’s degree or higher in AI, Computer Science, Mathematics, or a related field
5+ years of experience in data science or applied machine learning
Excellent communication skills, you can clearly explain complex ideas in non-technical terms and enjoy working closely with business stakeholders to solve problems together
Experienced in designing, deploying, and maintaining production ML systems, with solid software engineering and ML principles
Strong Python and SQL skills
Able to define the long-term vision and technical architecture for ML solutions within your domain
Experience with Docker, Kubernetes, and CI is a plus

Picnic Perks

🫱🏼‍🫲🏾 Teamwork makes the dream work

With more than 80 nationalities across 3 countries, you’ll be part of a diverse company with plenty of cool stuff to get involved with, from board game evenings to after-work drinks to our company ski trip and more!

💡 Make a difference

You’ll work in an awesome startup environment with the freedom to drive your own projects and create a visible impact. Our fully electric vehicles and sustainable business model mean you’ll also be contributing to making the world a better place!

🥗 Fresh Lunch, coffee, and snacks

Our offices are equipped with fully-fledged coffee bars and a kitchen and chefs. They prepare delicious fresh and warm lunches every day so you can keep your energy up.

🚲 Health insurance discount & bike plan

We have a partnership with CZ (a health insurance provider). Picnic employees get a discount on CZ insurance packages between 5% and 15%. Furthermore, through our partnership with Lease a Bike, you can rent-to-own a new (e)bike at a discounted rate

🌎 Relocation

If you’re moving from another country to join Picnic we make it as smooth as possible for you. We’ll cover your flight costs for you and your partner and kids, your first month's rent and moving costs (up to €2000), and help you with the 30% tax ruling setup and application.

📆 All the rest

At Picnic you get 25 holidays, we cover your travel expenses and offer a pension plan. And your phone and laptop are on us, as well.

A bit about us

When you join Picnic, you’re joining the shopping revolution, delivering groceries to millions of people across Europe, and we’re growing fast. Think super fresh products and personal service, but in a modern, sustainable way. The tech team at Picnic is at the core of Picnic. From deep learning models to forecast orders to delivery algorithms to warehouse logistics: we’ve built it all from the ground up. You’ll thrive here if you’re a problem solver with a pro-active mindset who’s not afraid to be challenged daily.

Commitment to equal opportunities

Picnic is an equal opportunity employer—this means that all decisions regarding applications will be based on qualifications and merit. Applicants will be regarded independently of age, gender identity or expression, sexual orientation, ethnicity, skin color, civil status, religious beliefs, physical or mental disability, or any other factors protected by law.

At Picnic, we celebrate and value our differences and are committed to building a safe and inclusive working environment where everyone can be themselves.

","hiringOrganization":{"@type":"Organization","name":"Picnic","sameAs":"https://picnic.app/"},"jobLocation":{"@type":"Place","address":{"@type":"PostalAddress","addressLocality":"Amsterdam, North Holland, Netherlands","addressCountry":"The Netherlands","addressRegion":"Europe"}}}},{"@type":"ListItem","position":46,"item":{"@type":"JobPosting","title":"Senior Machine Learning Engineer","datePosted":"2025-08-14","description":"

Oracle Health AI (OHAI) is at the forefront of transforming healthcare through advanced artificial intelligence and machine learning technologies. Our mission is to leverage Oracle’s leading cloud infrastructure, data assets, and deep healthcare expertise to create intelligent solutions that improve patient outcomes, streamline clinical workflows, and empower healthcare organizations worldwide. By integrating generative AI with robust data platforms, OHAI is building next-generation products that enable smarter, faster, and more personalized healthcare experiences - for providers, payers, and patients alike. Join us on our journey to bring cutting-edge technology to some of the world’s most meaningful and impactful challenges in healthcare.

Qualifications and Experience:

3-5 or 5+ years of experience working as a machine learning engineer delivering products in real world applications.
Demonstrated experience in designing and implementing scalable ML solutions, frameworks and pipelines for production.
Demonstrated experience in architecture design, deployment/monitoring, API and service engineering, workflow and tooling development.
Demonstrated experience in leveraging LLMs (such as code assist) to accelerate the above development activities.
Good technical understanding of Large Language Model, Machine Learning / Deep Learning architectures like Transformers, training methods, and optimizers.
Proven experience in coaching teams on engineering practices and PR reviews.
Commitment to staying up to date with the field and applying latest technologies to solve complex business problems and bringing them into production.

Preferred Qualifications:

Knowledge of healthcare and experience delivering healthcare AI products are a significant plus.
Having referrable products delivered before is a significant plus.

Education:

Masters or bachelor’s in computer science or related field with 3-5 or 5+ years relevant experience

Responsibilities

Responsibilities:

AI Product Development: Partner with product managers to translate business and healthcare requirements into actionable AI projects.
Technical Leadership: Collaborate with technical leaders and multinational AI teams to deliver high-impact features and services on schedule.
Cross-Functional Collaboration: Engage with both internal medical experts and customers to deeply understand healthcare contexts and inform AI solution development.
Project Delivery: Drive projects from concept to production, participating in planning, review, and retrospective meetings.
System Architecture and Infrastructure: Design and build scalable systems to support data processing, training, and deployment of generative AI models, while efficiently managing compute resources.
Deployment and Monitoring: Automate deployment of generative models to production and set up monitoring to track their performance, reliability, and operational health.
API and Service Engineering: Develop performant, secure APIs and services that enable seamless integration and scalable access to generative AI model capabilities.
Development Workflow and Tooling: Create tools and workflows that ensure experiment reproducibility, dataset management, and smooth collaboration throughout the model lifecycle.
Software Engineering Best Practices: Apply software engineering standards - such as modular code, testing, and documentation - to ensure maintainability and stability of ML systems.
Hands-on Programming and Code Review: Perform day to day programming task, deliver production quality codes, do PR reviews and set bars for PR review process, advocating for maintainability and robustness.
Mentorship: Lead and mentor both junior and senior applied scientists, fostering growth and technical excellence.

#LI-DNI

Career Level - IC3

As a world leader in cloud solutions, Oracle uses tomorrow’s technology to tackle today’s challenges. We’ve partnered with industry-leaders in almost every sector—and continue to thrive after 40+ years of change by operating with integrity.

We know that true innovation starts when everyone is empowered to contribute. That’s why we’re committed to growing an inclusive workforce that promotes opportunities for all.

Oracle careers open the door to global opportunities where work-life balance flourishes. We offer competitive benefits based on parity and consistency and support our people with flexible medical, life insurance, and retirement options. We also encourage employees to give back to their communities through our volunteer programs.

We’re committed to including people with disabilities at all stages of the employment process. If you require accessibility assistance or accommodation for a disability at any point, let us know by emailing accommodation-request_mb@oracle.com or by calling +1 888 404 2494 in the United States.

Oracle is an Equal Employment Opportunity Employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, national origin, sexual orientation, gender identity, disability and protected veterans’ status, or any other characteristic protected by law. Oracle will consider for employment qualified applicants with arrest and conviction records pursuant to applicable law.

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About Faculty

At Faculty, we transform organisational performance through safe, impactful and human-centric AI.

With more than a decade of experience, we provide over 350 global customers with software, bespoke AI consultancy, and Fellows from our award winning Fellowship programme.

Our expert team brings together leaders from across government, academia and global tech giants to solve the biggest challenges in applied AI.

Should you join us, you’ll have the chance to work with, and learn from, some of the brilliant minds who are bringing Frontier AI to the frontlines of the world.

We operate a hybrid way of working, meaning that you'll split your time across client location, Faculty's Old Street office and working from home depending on the needs of the project. For this role, you can expect to be client-side for up-to three days per week at times and working either from home or our Old street office for the rest of your time.

What You'll Be Doing

Working in our Defence business unit You will design, build, and deploy production-grade software, infrastructure, and MLOps systems that leverage machine learning. The work you do will help our customers solve a broad range of high-impact problems in the defence and national security space - examples of which can be found here

You are engineering-focused, with a keen interest and working knowledge of operationalised machine learning. You have a desire to take cutting-edge ML applications into the real world. You will develop new methodologies and champion best practices for managing AI systems deployed at scale, with regard to technical, ethical and practical requirements. You will support both technical and non-technical stakeholders to deploy ML to solve real-world problems. To enable this, we work in cross-functional teams with representation from commercial, data science, product management and design specialities to cover all aspects of AI product delivery.

The Machine Learning Engineering team is responsible for the engineering aspects of our customer delivery projects. As a Machine Learning Engineer, you’ll be essential to helping us achieve that goal by:

Building software and infrastructure that leverages Machine Learning;
Creating reusable, scalable tools to enable better delivery of ML systems
Working with our customers to help understand their needs
Working with data scientists and engineers to develop best practices and new technologies; and
Implementing and developing Faculty’s view on what it means to operationalise ML software.

We’re a rapidly growing organisation, so roles are dynamic and subject to change. Your role will evolve alongside business needs, but you can expect your key responsibilities to include:

Working in cross-functional teams of engineers, data scientists, designers and managers to deliver technically sophisticated, high-impact systems.
Leading on the scope and design of projects
Offering leadership and management to more junior engineers on the team
Providing technical expertise to our customers
Technical Delivery

Who We're Looking For

At Faculty, your attitude and behaviour are just as important as your technical skill. We look for individuals who can support our values, foster our culture, and deliver for our organisation.

We like people who combine expertise and ambition with optimism -- who are interested in changing the world for the better -- and have the drive and intelligence to make it happen. If you’re the right candidate for us, you probably:

Think scientifically, even if you’re not a scientist - you test assumptions, seek evidence and are always looking for opportunities to improve the way we do things.
Love finding new ways to solve old problems - when it comes to your work and professional development, you don’t believe in ‘good enough’. You always seek new ways to solve old challenges.
Are pragmatic and outcome-focused - you know how to balance the big picture with the little details and know a great idea is useless if it can’t be executed in the real world.

To succeed in this role, you’ll need the following - these are illustrative requirements and we don’t expect all applicants to have experience in everything (70% is a rough guide):

Understanding of and interest in the full machine learning lifecycle, including deploying trained machine learning models developed using common frameworks such as Scikit-learn, TensorFlow, or PyTorch
Understanding of the core concepts of probability and statistics and familiarity with common supervised and unsupervised learning techniques
Experience in Software Engineering including programming in Python.
Technical experience of cloud architecture, security, deployment, and open-source tools. Hands-on experience required of at least one major cloud platform
Demonstrable experience with containers and specifically Docker and Kubernetes
Comfortable in a high-growth startup environment.
Outstanding verbal and written communication.
Excitement about working in a dynamic role with the autonomy and freedom you need to take ownership of problems and see them through to execution

What we can offer you:

The Faculty team is diverse and distinctive, and we all come from different personal, professional and organisational backgrounds. We all have one thing in common: we are driven by a deep intellectual curiosity that powers us forward each day.

Faculty is the professional challenge of a lifetime. You’ll be surrounded by an impressive group of brilliant minds working to achieve our collective goals.

Our consultants, product developers, business development specialists, operations professionals and more all bring something unique to Faculty, and you’ll learn something new from everyone you meet.

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Iterable is the leading AI-powered customer engagement platform that helps leading brands like Redfin, SeatGeek, Priceline, Calm, and Box create dynamic, individualized experiences at scale. Our platform empowers organizations to activate customer data, design seamless cross-channel interactions, and optimize engagement—all with enterprise-grade security and compliance. Today, nearly 1,200 brands across 50+ countries rely on Iterable to drive growth, deepen customer relationships, and deliver joyful customer experiences.

Our success is powered by extraordinary people who bring our core values—Trust, Growth Mindset, Balance, and Humility—to life. We foster a culture of innovation, collaboration, and inclusion, where ideas are valued and individuals are empowered to do their best work. That’s why we’ve been recognized as one of Inc’s Best Workplaces and Fastest Growing Companies, and were recognized on Forbes’ list of America’s Best Startup Employers in 2022. Notably, Iterable has also been listed on Wealthfront’s Career Launching Companies List and has held a top 10 ranking on the Top 25 Companies Where Women Want to Work.

With a global presence—including offices in San Francisco, New York, Denver, London, and Lisbon, plus remote employees worldwide—we are committed to building a diverse and inclusive workplace. We welcome candidates from all backgrounds and encourage you to apply. Learn more about our story and mission on our Culture and About Us pages. Let’s shape the future of customer engagement together!

How you will make an impact:

We’re looking for a talented Senior Machine Learning Engineer to join a cross-functional machine learning team shaping the future of our platform’s AI capabilities. In this role, you’ll architect and develop robust systems for feature engineering and large-scale model training — collaborating across teams, navigating complex data challenges, and guiding technical direction.

This is an exceptional opportunity for someone with a strong platform mindset who is passionate about building end-to-end ML workflows, enjoys tackling real-world data problems, and thrives on ownership from ideation through to deployment. You’ll play a pivotal part in designing reusable, scalable ML infrastructure, enabling teams to accelerate experimentation and bring intelligent features to life. While specific domain expertise in certain ML methods is a plus, what matters most is your ability to identify impactful opportunities, prototype new solutions, and continuously advance our platform’s machine learning capabilities.

One of our core values is a growth mindset and Iterable is a company where everyone can grow. If this is a role that excites you, please do apply as we value applicants for the skills they bring beyond a job description.

How You Will Make a Difference:

Independently lead large-scale machine learning initiatives—delivering capabilities for scalable feature engineering, data processing, and model training on Databricks.
Design, build, and deploy machine learning models that enable our partners to reach the right user with the right message at the right time.
Own the complete lifecycle of ML platform features: from requirements gathering and architecture, through implementation, deployment, and post-launch support.
Shape architectural decisions aimed at building robust, reusable, and highly available ML infrastructure that raises the bar for engineering and data science excellence.
Mentor colleagues through code reviews, technical design sessions, and knowledge sharing, helping grow a strong culture of engineering rigor and learning.

We Are Looking for People Who:

Have 5+ years of experience in machine learning engineering, data infrastructure, or platform engineering, preferably in a SaaS environment.
Demonstrate a strong track record leading multi-stakeholder projects that deliver platform features, scalable ML tooling, or end-to-end training systems.
Show proficiency with Python (with a preference for experience in distributed data processing environments like Databricks, Spark, or similar platforms).
Bring hands-on experience with large-scale data pipelines, distributed systems, and cloud data storage (Databricks Delta, Spark, Kafka, Postgres, etc.).
Exhibit a product-minded approach: comfortable partnering with product managers and data practitioners to balance trade-offs across usability, scalability, and complexity.
Possess curiosity and adaptability to master new ML and data technologies, frameworks, and best practices.
Communicate and collaborate effectively within remote and distributed teams.

Bonus Points

Experience building or operating ML platforms on Databricks.
Scala development experience
Familiarity with ML workflow orchestration tools (e.g., MLflow, Kubeflow, Airflow) and interest in automating model development, testing, and deployment.
Exposure to generative AI or large language model workflows within an agentic or conversational UX context.
Experience designing developer-facing APIs or tools to empower other ML engineers or data scientists.
Success working in remote-first or globally distributed engineering organizations.

Perks & Benefits:

Competitive salaries, meaningful equity, & 401(k) plan
Medical, dental, vision, & life insurance
Balance Days (additional paid holidays)
Fertility & Adoption Assistance
Paid Sabbatical
Flexible PTO
Monthly Employee Wellness allowance
Monthly Professional Development allowance
Pre-tax commuter benefits
Complete laptop workstation

The US base salary range for this position at the start of employment is $133,500 - $212,000. Within this range, individual pay is determined by specific US work location, as well as additional factors, including job-related skills, experience, relevant education or training, and internal equity considerations.

Please note that the range listed above reflects only base salary. The total compensation package includes variable pay (where applicable), equity, plus a range of benefits, including medical, dental, vision, and financial. In addition, we offer perks such as generous stipends for health & fitness and learning & development, among others.

Recruitment Disclaimer:

Please be aware that Iterable, Inc. (“Iterable”) and our official professional recruiting agencies and platforms do not:

Send job offers from free email services like Gmail, Yahoo mail, Hotmail, etc.
Request money, fees, or payment of any kind from prospective candidates to apply to Iterable, for employment, or for the recruitment process (e.g. for home office supplies, or training, etc.).
Request or require personal documents like bank account details, tax forms, or credit card information as part of the recruitment process prior to the candidate signing an engagement letter or an employment contract with Iterable.

You may see all job vacancies on our official Iterable channels:

Official Iterable website, Careers page: https://iterable.com/careers/
Official LinkedIn Jobs page: https://www.linkedin.com/company/iterable/jobs/

Iterable is not affiliated in any way to these impostors and we hereby confirm that such individuals/entities are not authorized, encouraged, or sponsored to act on behalf of Iterable. Such job opportunities are entirely fake and not valid. Therefore, please disregard any written or oral request for a job offer or an interview that you believe is or might be fraudulent or suspicious and immediately reach out to us via email at talent-ops@iterable.com upon receiving a suspicious job offer.

Criminal and/or civil liabilities may arise from such actions, and Iterable expressly reserves the right to take legal action, including criminal action, against such individuals/entities whenever such phenomena occur. In any case, please note that under no circumstances shall Iterable and any of its affiliates be held liable or responsible for any claims, losses, damages, expenses or other inconvenience resulting from or in any way connected to the actions of these impostors.

Iterable is an Equal Employment Opportunity employer that proudly pursues and hires a diverse workforce. Iterable does not make hiring or employment decisions on the basis of race, color, religion or religious belief, ethnic or national origin, nationality, sex, gender, gender-identity, sexual orientation, disability, age, military or veteran status, or any other basis protected by applicable local, state, or federal laws or prohibited by Company policy. Iterable also strives for a healthy and safe workplace and strictly prohibits harassment of any kind. Pursuant to the San Francisco Fair Chance Ordinance and other similar state laws and local ordinances, and its internal policy, Iterable will also consider for employment qualified applicants with arrest and conviction records.

","hiringOrganization":{"@type":"Organization","name":"Iterable","sameAs":"https://iterable.com/"},"jobLocation":{"@type":"Place","address":{"@type":"PostalAddress","addressLocality":"REMOTE - US","addressCountry":"United States","addressRegion":"North America"}}}},{"@type":"ListItem","position":49,"item":{"@type":"JobPosting","title":"Senior Machine Learning Engineer","datePosted":"2025-08-17","description":"

Take your career to new heights with Loopio! 🚀✨

Loopio is a workplace that unleashes learning & growth opportunities for our Loopers. We provide autonomous, challenging work that allows each employee to master their craft. We attract and retain people who are naturally curious, have grit and are eager to grow and build their careers. At Loopio, we genuinely support each other, because true success comes from working as #oneteam.

We are looking for an experienced Senior Machine Learning Engineer to join the Strategic Insights team within Engineering, building and supporting ML-driven features that empower customers with actionable insights to improve proposal quality, win rates, and team productivity. This role focuses on enhancing dashboard usability, integrating tailored recommendations, and increasing efficiency through analytics while showcasing Loopio’s ROI to executives. You’ll work across the platform portfolio, leveraging NLP and GenAI to develop solutions like automated language detection, intelligent project import, and search enhancements. This is a unique opportunity to join a growing team of creative and passionate individuals committed to solving real-world problems with modern AI practices.

You will partner closely with Product Managers, Architects and Data Scientists to use Machine Learning techniques to help us take Loopio’s user value to the next level.

This role requires close collaboration with teams across Canada, the UK, and India. To accommodate the time zone differences, you will be expected to work from 11 am to 7:30 pm IST.

What You’ll Be Doing

End-to-End ML & NLP Deployment: Design, build, and optimize scalable ML systems for NLP applications, including fine-tuning large language models (LLMs), deploying transformer-based architectures, and optimizing inference for real-time and batch workloads. Architect distributed ML solutions for large-scale data processing and efficient retrieval-augmented generation (RAG).
MLOps & Cloud Infrastructure: Implement best practices for ML lifecycle management, including model versioning, monitoring, and automation. Build robust CI/CD pipelines, integrate with feature stores and vector databases, and deploy models on cloud platforms (preferably AWS).
Software Engineering & Microservices: Develop high-performance ML systems using Python, deep learning frameworks (TensorFlow, PyTorch), and distributed computing frameworks (Spark, Databricks). Build scalable microservices and APIs for real-time model serving using containerized (Docker, Kubernetes) and serverless (AWS Lambda, Kinesis) architectures. Strong Object Oriented Programming fundamentals to build modular and reusable code.
Cross-Functional Collaboration: Work closely with Data Scientists, Engineers, and Product teams to productionize NLP models, ensuring alignment with business needs and maintaining robust, scalable AI-driven solutions.

What You’ll Bring to the Team

ML & NLP Expertise: 4+ years of experience in ML engineering, with strong expertise in NLP, LLMs, transformers, and RAG. Proven ability to fine-tune, optimize, and deploy large-scale NLP models.
MLOps & Cloud Engineering: Hands-on experience with ML pipeline automation, monitoring, and deployment using cloud services. Strong background in data engineering for scalable AI systems, including structured (MySQL, PostgreSQL) and NoSQL (Redis, Cassandra) databases.
Scalable Systems & Distributed Computing: Experience with performance optimization techniques for ML inference, distributed computing (Spark, Presto, Databricks), and real-time/batch processing pipelines.
Software Development & Microservices: Strong Python development skills, experience with API-driven architectures (REST, gRPC), and ability to build robust, maintainable ML services.
Collaborative Problem Solving: Ability to work cross-functionally with product, engineering, and design teams effectively to translate business needs into AI solutions. Skilled at fostering alignment, sharing knowledge, and co-creating strategies that drive measurable impact.

Where You’ll Work 📍

Loopio is a remote-first workplace because we recognize the advantages of working flexibly. We are HQ’d in Canada, with established hub regions around the world where we hire from.
Our employees (or Loopers, as we call ourselves!) live and work in 🇨🇦 Canada (British Columbia and Ontario), 🇬🇧 London, and 🇮🇳 India (specifically in Gujarat, Maharashtra, and Bengaluru).
Our India/UK hub employees work according to the business hours stated in the job description above. This is intentionally designed to enable our global teams to have overlapping hours for collaboration.
You’ll collaborate with your teams virtually across the UK, India, and North America (we’re just a Zoom call and Slack message away!) with core sync hours and focus time for headsdown work 🙇🏾 during the workday
We encourage asynchronous collaboration to effectively work as a global #OneTeam!

Why You’ll ❤️ Working at Loopio

Your manager supports your development by providing ongoing feedback and regular 1-on-1s; we leverage Lattice for our 1:1s and performance conversations
You will have the opportunity to elevate 🪄 your craft and the opportunity to explore your creativity with a dedicated professional mastery allowance for more learning support! We encourage experimentation and innovative thinking to drive business impact.
We offer a wide range of health and wellness benefits to support your physical and mental well-being, starting day 1️⃣ with Loopio.
We’ll set you up to work remotely with a MacBook laptop 🍏, a monthly phone and internet subsidy, and a work-from-home budget to help get your home office all set up.

You’ll be joining a supportive culture that has thoughtfully built out opportunities for connections in a remote first environment.
Participate in 🎤 townhalls, AMA (Ask-Me-Anything), and quarterly celebrations to celebrate the big wins and milestones as #oneteam!

Our four active Employee Resource Groups offer opportunities for employees to learn and connect year-round.
You’ll be a part of an award-winning workplace 🏆with an opportunity to make a big impact on the business.

Questioning your qualifications? Read this ‼️ Hi there, we recognize that all too often, potential candidates don’t apply for a position simply because they don’t hit every single criteria included in the job description—particularly members of underrepresented groups.

Whether or not your experience ✅ checks off all the boxes on a job posting, we still encourage you to apply to ensure that your application receives a review from our team. We understand that a resume can only showcase so much during the applicant stage, so we've created prompts in the application for you to share more about yourself. If you've made a career transition (or a few!), you’re self taught in a new role, or you have skills/experience you’d like to highlight, we want to hear more about what you could bring to the table.

AI in Recruitment 👩🏻‍💻 At Loopio, we leverage artificial intelligence (AI) technology to enhance our recruitment process. These tools assist with tasks such as resume screening, drafting preliminary job descriptions, generating initial interview questions, and occasionally sourcing prospective candidates. However, AI is never used to make final hiring decisions; our use of AI serves to support repetitive and administrative tasks in order to streamline our hiring and recruitment workflows. We are committed to the responsible use of AI in our hiring practices, prioritizing both an improved candidate experience and operational efficiency. Our standardized hiring practices remain focused on reducing biases, with all key hiring decisions solely made by our team. We continuously review and refine our hiring practices to align with industry best practices and evolving legal guidelines

Loopio is an equal opportunity employer that is deeply committed to building equitable workplaces that are diverse and inclusive. We actively encourage candidates from all backgrounds and lifestyles to consider us as a future employer. Please contact a member of our Talent Experience team (work@loopio.com) should you require accommodations at any point during our virtual interview processes.

","hiringOrganization":{"@type":"Organization","name":"Loopio","sameAs":"https://loopio.com/"},"jobLocation":{"@type":"Place","address":{"@type":"PostalAddress","addressLocality":"Bangalore","addressCountry":"India","addressRegion":"Asia/Pacific"}}}},{"@type":"ListItem","position":50,"item":{"@type":"JobPosting","title":"Senior Machine Learning Engineer","datePosted":"2025-08-18","description":"

Conviva helps the world’s top brands to identify and act on growth opportunities across mobile and web apps, video streaming services, and Agentic AI experiences. Our platform delivers real-time performance analytics to transform every customer interaction into actionable insight, connecting experience, engagement, and technical performance to business outcomes. By analyzing client-side session data from all users as it happens, Conviva reveals not just what happened, but how long it lasted and why it mattered—surfacing behavioral and experience patterns that give teams the context to retain more customers, resolve issues faster, and grow revenue.

As a Senior Machine Learning Engineer, you will play a key role in advancing our AI initiatives and contributing to the development of our Real-Time Performance Analytics Platform. You will work across a broad range of ML technologies to create innovative, customer-focused solutions.

In this role, you’ll collaborate closely with vertical product teams to design and deploy ML models directly within product pipelines. You’ll work with other team members to build scalable ML tooling and infrastructure, combining research, product integration, and data development.

What Success Will Look Like:

Design, develop, and deploy machine learning models that power AI-based features across a large-scale data analytics platform.

Own ML systems end-to-end, from data ingestion and feature engineering to training, deployment, monitoring, and iteration in production environments.

Build and maintain ML infrastructure and MLOps pipelines for scalable, repeatable model development and deployment.

Collaborate with infrastructure and backend engineers and product teams to ensure ML solutions are aligned with platform performance and user needs.

Continuously evaluate model performance using robust testing, monitoring, and alerting systems for data and model drift.

Identify opportunities to improve system robustness and proactively detect data, device, or user level anomalies through intelligent alert mechanisms.

Drive technical decisions, code quality, and best practices for ML engineering within a small, high-impact team.

Who You Are and What You've Done:

PhD in Computer Science, Machine Learning, or a related technical field; OR a Master’s degree in Computer Science or Machine Learning with 2+ years of experience in machine learning engineering or a related field.

Proven track record of owning the ML lifecycle: data pipelines, model training, validation, deployment, monitoring, and optimization.

Strong software engineering background with 5+ years of experience and proficiency in modern languages like Python, Rust, Java, or Scala.

Experience with big data frameworks (e.g., RAY, Spark, Flink) and ML infrastructure (e.g., MLflow, Kubeflow, or custom pipelines).

Strong cross-functional collaboration skills and a bias toward proactive problem-solving, continuous improvement, and system-level thinking.

What Would Make You Stand Out (Bonus Points):

Experience with real-time data processing and analytics.
Familiarity with time series analysis and forecasting techniques.
Background in building AI-powered alerts, anomaly detection, or similar AI driven applications.
Familiarity with cloud-based ML deployment and MLOps best practices.

*This position will be based in our Foster City, CA office.

The expected salary range for this full-time position is $180,000 - $220,000 + equity + benefits. The actual level and compensation are determined by several factors, such as your qualifications, professional background, and relevant experience.

Privately held, Conviva is headquartered in Silicon Valley, California with offices and people around the globe. For more information, visit us at www.conviva.com. Join us to help extend our leadership position in big data streaming analytics to new audiences and markets!

","hiringOrganization":{"@type":"Organization","name":"Conviva","sameAs":"https://www.conviva.com/"},"jobLocation":{"@type":"Place","address":{"@type":"PostalAddress","addressLocality":"Foster City, CA","addressCountry":"United States","addressRegion":"North America"}}}}]}

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