{"@context":"https://schema.org","@type":"ItemList","name":"Find Machine Learning Engineer Jobs - Apply Now","description":"Explore the latest Machine Learning Engineer job openings. Apply now to kickstart your career in AI and data science. Find top companies hiring Machine Learning Engineers.","itemListElement":[{"@type":"ListItem","position":1,"item":{"@type":"JobPosting","title":"Machine Learning Engineer","datePosted":"2025-09-24","description":"

This is a remote position.

\n\n\n\n\n\n Responsibilities
\n\n\n\n\n

You will be responsible for designing, implementing, monitoring and maintaining our machine learning systems
You will be working in a highly-collaborative environment with other experts in data science and engineering
Transform business problems into data problems
Research and build statistical/machine-learning models
Perform Exploratory Data Analysis and Statistical Analysis; clearly present the results of an analysis to customers and management

\n\n\n
\n

Requirements

\n\n\n\n\n\n\n Must Have Skills:
\n\n

Master’s Degree in Computer Science, Mathematics, Statistics or a related quantitative field with a focus on Machine Learning or Deep Learning. Ph.D. preferred
3+ years of professional experience as a Machine Learning Engineer/Data Scientist; in a product development setting
Hands-on experience with software development, including translating ML models into scalable production services
Good intuitive understanding of machine learning algorithms and practical experience building models with incremental/iterative approach
Strong in Python
Experience in implementing machine learning algorithms using APIs/libraries from scikit-learn, H2O, MLlib and TensorFlow
Hands-on experience with software development, including translating ML models into scalable production services
Experience in working with large data sets and pipelines, distributed systems for machine learning using frameworks such as Apache Spark
Excellent verbal and written communication skills
You take complete ownership of your work and are self-driven

\n\n\n\n\n\n
\n\n\n\n\n\n\n\n\n\n\n\n
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","hiringOrganization":{"@type":"Organization","name":"Marktine Technology Solutions Pvt Ltd","sameAs":"https://marktine.com/"},"jobLocation":{"@type":"Place","address":{"@type":"PostalAddress","addressLocality":"Remote"}}}},{"@type":"ListItem","position":2,"item":{"@type":"JobPosting","title":"Machine Learning Engineer","datePosted":"2025-09-24","description":"Company Overview

Join Navatech Labs, where innovation meets excellence. Our forward-thinking team is dedicated to\nadvancing the construction industry through artificial intelligence. As a vital member of our AI team,\nyou will be at the forefront of groundbreaking projects utilising GenAI, Natural Language\nProcessing (NLP), Large Language Model (LLM) training and tuning, MLOps, and Cloud

Key Responsibilities

Develop and implement innovative NLP algorithms and models to address complex\nbusiness challenges, Utilise large language models (LLMs) for natural language processing\nand generative AI tasks. Develop advanced generative AI solutions using open-source\nLLMs.
Participate in the training and fine-tuning of Large Language Models to ensure optimal\nperformance and accuracy. Assess machine learning model performance, iterate on\nimprovements, and apply best practices for model validation.
Collaborate with cross-functional teams to establish effective MLOps practices, ensuring\nseamless deployment, monitoring, and management of machine learning models. Integrate\nAI solutions into existing platforms, working closely with various teams.
Leverage cloud platforms for scalable and efficient machine learning solutions, utilising\nservices like AWS or Google Cloud.

Requirements

Professional Experience

Proven experience (2-3 years) in developing and deploying machine learning models, with\na focus on NLP.
Experience in developing and deploying chatbot or conversational AI systems.\n

Technical Skills

Strong programming skills in languages such as Java and Python, and proficiency with ML\nframeworks (e.g., TensorFlow, PyTorch).
Experience in using LLMs for natural language processing or generative AI tasks.
Experience with MLOps tools and practices for model deployment, monitoring, and\nautomation.
Familiarity with cloud services and infrastructure for machine learning applications.
Strong understanding of AI, Generative AI patterns such as RAG and prompt engineering\ntechniques.
Excellent problem-solving skills and a team-oriented mindset.
Strong communication skills to convey complex technical concepts to both technical and\nnon-technical stakeholders.

Benefits

What We Offer

Competitive salary and benefits package.
Opportunity to work on cutting-edge AI projects

https://www.linkedin.com/posts/cyberamyntas_edgeai-aidevelopment-languagemodels-activity-7190672496885485570-WOGK

Collaborative and inclusive team environment.

https://www.linkedin.com/posts/navatech-group_navapulse2023-annualparty-activity-7163411226117586944-l_Fx

Continuous learning and professional development opportunities.

","hiringOrganization":{"@type":"Organization","name":"Navatech","sameAs":"https://navatech.ai/"},"jobLocation":{"@type":"Place","address":{"@type":"PostalAddress","addressLocality":"Bengaluru, India","addressCountry":"India","addressRegion":"Asia/Pacific"}}}},{"@type":"ListItem","position":3,"item":{"@type":"JobPosting","title":"Machine Learning Engineer - Global E-commerce Recommendation/Search","datePosted":"2025-09-24","description":"The Data-E-commerce team oversees algorithmic and corresponding engineering work in the e-commerce business. Our responsibilities encompass not only utilizing recommendation and search algorithms to help users discover appealing products but also implementing risk control and content safety algorithms to identify malicious sellers/influencers and violations in products/videos/live streams, ensuring a secure shopping experience. Furthermore, we are involved in constructing intelligent customer service technology and large-scale product knowledge graphs, aiming to enhance efficiency across various transaction processes. Through operations optimization and intelligent supply chain algorithms, we work to improve logistics efficiency.
\n
\nResponsibilities:
\n- Work in a team to conduct cutting-edge research in machine learning algorithms, such as retrieval and recommendation algorithms.
\n- Participate in building large-scale (10 million to 100 million) e-commerce recommendation algorithms and systems, including commodity recommendations, live stream recommendations, short video recommendations etc in TikTok.
\n- Build long and short term user interest models, analyze and extract relevant information from large amounts of various data and design algorithms to explore users' latent interests efficiently.
\n- Apply machine learning algorithms to improve the different business scenarios, such as search ranking, natural language and video understanding, and trust and safety.","hiringOrganization":{"@type":"Organization","name":"TikTok","sameAs":"https://www.tiktok.com/"},"jobLocation":{"@type":"Place","address":{"@type":"PostalAddress","addressLocality":"Seattle, Washington, United States","addressCountry":"United States","addressRegion":"North America"}}}},{"@type":"ListItem","position":4,"item":{"@type":"JobPosting","title":"Senior Machine Learning Engineer - TikTok Short Video Content Understanding/Multimodal Recommendation","datePosted":"2025-09-24","description":"Our team's mission is to empower content understanding for TikTok Short Video business. We focus on cutting-edge research in content understanding and the development of advanced LLM/MLLM algorithms and applications, including generative recommendation, weakly-supervised learning, few-shot classification, video tagging, multi-task learning, multilingual learning, multimodal pretraining, and more. We aim to succeed both in driving measurable business impact (e.g., recommendation metrics) and delivering state-of-the-art research outputs.
\n
\nResponsibilities
\n1. Lead multimodal algorithm development for TikTok’s short-video business, explore applications of multimodal technologies in recommendation systems and other scenarios to improve key business metrics.
\n2. Conduct cutting-edge research in multimodal and MLLM technologies, design advanced algorithms to solve business requirements while achieving technical breakthroughs.
\n3. Drive engineering deployment and implementation, ensuring model stability, scalability, and efficiency in production environments.
\n4. Focus on key areas including (but not limited to):
\n- General AI platform design and development, including few-shot/zero-shot on MLLM, AI-labeling, auto prompting, active-learning, continue pretraining and RL.
\n- Integration of content understanding with recommendation systems (e.g., UGC ecosystems, cold start, interest exploration, comment understanding).
\n- Leveraging multimodal techniques to develop next-generation recommendation systems, such as generative models and end-to-end approaches.","hiringOrganization":{"@type":"Organization","name":"TikTok","sameAs":"https://www.tiktok.com/"},"jobLocation":{"@type":"Place","address":{"@type":"PostalAddress","addressLocality":"San Jose, California, United States","addressCountry":"United States","addressRegion":"North America"}}}},{"@type":"ListItem","position":5,"item":{"@type":"JobPosting","title":"Machine Learning Engineer","datePosted":"2025-09-24","description":"

Company Description

Sia is a next-generation, global management consulting group. Founded in 1999, we were born digital. Today our strategy and management capabilities are augmented by data science, enhanced by creativity and driven by responsibility. We’re optimists for change and we help clients initiate, navigate and benefit from transformation. We believe optimism is a force multiplier, helping clients to mitigate downside and maximize opportunity. With expertise across a broad range of sectors and services, our 3,000 consultants serve clients worldwide from 48 locations in 19 countries. Our expertise delivers results. Our optimism transforms outcomes.

Job Description

What you will do
\nAs an expert in the field of Machine Learning Engineering you will be responsible for the growth of our Data team, both professionally as well as in size. You will be in charge of shaping and executing the future of your expertise within Sia. You will work on client projects as well as on building our own Sia AI solutions, together with our Dutch team of Data Scientists, our French Data Engineering team, and other business units of Sia Global.

Your Responsibilities Include:

Leading an internal team towards the development of AI products;
Working in a multidisciplinary team on client projects as an expert on your subject;
Making architectural and design decisions for cloud environments;
Building production level ML/AI solutions with solid software engineering;
Guiding Data Scientists to scale up their models into production (parallelizing, optimizing, tuning, testing, and wrapping);
Giving trainings, leading internal meetings and organizing external events;
Participating in team meetings and workshops with clients;
Writing blog articles, presenting at conferences and sending out press releases on the subject that you lead.

Who you will work with
\nThe Data Science team is young, diverse and growing (10+). You will join a team that will challenge you and invest in your professional development. We have a flat structure and rely on the entrepreneurial spirit of our members: initiative is highly encouraged. We are striving for well-being, diversity and knowledge-sharing inside the team, so that we can grow together.

Who You Are

You are an established technical professional that wants to make the next step in their career, taking on more leadership responsibilities.
You have first-rate project management and time management skills.
You are a true problem solver, you turn complex issues into simple and impactful business solutions.
You are enthusiastic for applying Data Science/Engineering solutions to business problems.
You have excellent communication skills and can present complicated concepts in a synthetic way.
You have the ability to adapt rapidly and work on a range of different business areas within a challenging environment.
You have the ability to work collaboratively in a team environment.

In Return, You Can Expect:

An international company that gives importance to diversity, inclusion, employee well-being and corporate social responsibilities actions.
A great working atmosphere with friendly and professional colleagues where innovation and entrepreneurship are encouraged
A personal development plan with a regular follow-up as well training opportunities to develop yourself
A competitive salary with great advantages, like mobility budget, hospital insurance, performance -related bonus,...

Qualifications

MSc level education in Computer Science, Applied Mathematics, Artificial Intelligence, Embedded Systems or related field of study.
2-4 years of experience in building production-quality ML/Deep Learning pipelines and models.
Good understanding of Machine Learning fundamentals and strong knowledge in a specific domain (e.g., Computer Vision, Deep Learning, NLP).
Expert coding skills in Python and at least one of these languages: Scala, C++, Java.
Hands-on experience with database management languages (e.g., SQL, PostgreSQL).
Hands-on experience in cloud-based infrastructures (AWS/GCP/Azure).
Hands-on experience with Unix-based command line and DevOps tools (Git, Docker, Kubernetes).
Hands-on experience with big data technologies (e.g. Spark, Hadoop, Databricks).
Experience with coaching/mentoring other engineers.
Prior experience in Management Consulting is a strong plus.
Willingness to travel and work at local and international clients.
Fluency in spoken and written English is required.
Ability or strong willingness to be professionally proficient in the Dutch language.

Additional Information

We are unable to provide a work permit for this position

Sia is an equal opportunity employer. All aspects of employment, including hiring, promotion, remuneration, or discipline, are based solely on performance, competence, conduct, or business needs.

","hiringOrganization":{"@type":"Organization","name":"Sia","sameAs":"https://www.sia-partners.com"},"jobLocation":{"@type":"Place","address":{"@type":"PostalAddress","addressLocality":"Antwerp, Belgium","addressCountry":"Belgium","addressRegion":"Europe"}}}},{"@type":"ListItem","position":6,"item":{"@type":"JobPosting","title":"Machine Learning Engineer","datePosted":"2025-09-24","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

What you get to do in this role:

Contribute to the design, development, and evaluation of machine learning solutions, with exposure to large language models (LLMs) and modern AI techniques.
Support the development of prototypes and proof-of-concepts that demonstrate new AI capabilities and improve model performance.
Run experiments to assess model accuracy, generalization, and fairness across different datasets and tasks.
Help generate, clean, and curate datasets (synthetic and real-world) to improve training and evaluation pipelines.
Fine-tune and evaluate pre-trained models, applying techniques such as prompt engineering and retrieval augmentation under guidance from senior engineers.
Work closely with cross-functional teams (research, engineering, product) to deliver production-quality ML features.
Implement and follow established evaluation protocols, including testing for bias, robustness, and safety.
Develop and maintain training and deployment pipelines using containerized workflows and modern MLOps practices.
Contribute to responsible AI practices by applying transparency and compliance guidelines in day-to-day work.

Qualifications

Key Qualifications:

Experience in using AI Productivity tools such as Cursor, Windsurf, etc. is a plus or nice to have
Experience with methods of training and fine-tuning large language models, such as distillation, supervised fine-tuning, and policy optimization
2+ years of experience in machine learning, deep learning, or data science.
Proficiency in Python and JavaScript, with familiarity in ML frameworks such as PyTorch, TensorFlow, HuggingFace Transformers, and NumPy.
Experience with training and evaluating machine learning models; exposure to LLMs or foundation models is a plus.
Hands-on experience with dataset preparation, labelling, or data processing workflows.
Understanding of ML evaluation strategies, model optimization techniques, and awareness of responsible AI practices.
Familiarity with deploying ML models using inference platforms (e.g., ONNX, Triton) or cloud services.
Exposure to MLOps tools (e.g., MLflow, Docker, Kubernetes, CI/CD) for experiment tracking and deployment.
Strong communication skills with the ability to collaborate effectively with technical peers and share results clearly.
Knowledge of ServiceNow platform development and its integration with AI/ML solutions.

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":7,"item":{"@type":"JobPosting","title":"Principal Machine Learning Engineer, Ads Delivery","datePosted":"2025-09-24","description":"

About Pinterest:

Millions of people around the world come to our platform to find creative ideas, dream about new possibilities and plan for memories that will last a lifetime. At Pinterest, we’re on a mission to bring everyone the inspiration to create a life they love, and that starts with the people behind the product.

Discover a career where you ignite innovation for millions, transform passion into growth opportunities, celebrate each other’s unique experiences and embrace the flexibility to do your best work. Creating a career you love? It’s Possible.

Within the Ads Delivery team, we try to connect the dots between the aspirations of pinners and the products offered by our partners. In this role, you will be responsible for developing and executing a vision for the evolution of the Pinterest marketplace. You will design and implement systems that improve the ads delivery funnel, experiments that shape the utility function, auction mechanism design, ad allocation and for deriving new insights through analysis of the marketplace dynamics. In short, this is a unique position, where you’ll get the freedom to work to bring together pinners and partners in this unique marketplace.

\n\n

What You’Ll Do:

Build and improve backend systems and statistical models that underlay the marketplace to maximize value for Pinners, Partners and Pinterest.
Define and implement experiments to understand long term Marketplace effects.
Develop strategies to balance long and short term business objectives.
Drive multi-functional collaboration with peers and partners across the company to improve knowledge of marketplace design and operations.

\n\n

What We’Re Looking For:

MS or PhD degree in Computer Science, Statistics or related field.
8+ years of industry experience.
2+ years of experience leading projects/teams.
Strong software engineering and mathematical skills with knowledge of statistical methods.
Hands-on experience with large-scale online e-commerce systems is a plus.
Background in computational advertising is preferred, but not required.

\n\n

In-Office Requirement Statement:

We let the type of work you do guide the collaboration style. That means we're not always working in an office, but we continue to gather for key moments of collaboration and connection.
This role will need to be in the office for in-person collaboration 1-2 times/month, and therefore needs to be in a commutable distance from one of the following offices: San Francisco, Palo Alto, Seattle.

\n\n

Relocation Statement:

This position is not eligible for relocation assistance. Visit our PinFlex page to learn more about our working model.

\n\n

#Li-Hybrid

#Li-Sm4

At Pinterest we believe the workplace should be equitable, inclusive, and inspiring for every employee. In an effort to provide greater transparency, we are sharing the base salary range for this position. The position is also eligible for equity. Final salary is based on a number of factors including location, travel, relevant prior experience, or particular skills and expertise.

Information regarding the culture at Pinterest and benefits available for this position can be found here.

US based applicants only$294,000—$514,500 USD

Our Commitment To Inclusion:

\nPinterest is an equal opportunity employer and makes employment decisions on the basis of merit. We want to have the best qualified people in every job. All qualified applicants will receive consideration for employment without regard to race, color, ancestry, national origin, religion or religious creed, sex (including pregnancy, childbirth, or related medical conditions), sexual orientation, gender, gender identity, gender expression, age, marital status, status as a protected veteran, physical or mental disability, medical condition, genetic information or characteristics (or those of a family member) or any other consideration made unlawful by applicable federal, state or local laws. We also consider qualified applicants regardless of criminal histories, consistent with legal requirements. If you require a medical or religious accommodation during the job application process, please complete this form for support.","hiringOrganization":{"@type":"Organization","name":"Pinterest","sameAs":"https://www.pinterest.com/"},"jobLocation":{"@type":"Place","address":{"@type":"PostalAddress","addressLocality":"San Francisco, CA, US; Palo Alto, CA, US; Seattle, WA, US","addressCountry":"United States","addressRegion":"North America"}}}},{"@type":"ListItem","position":8,"item":{"@type":"JobPosting","title":"Machine Learning Engineer","datePosted":"2025-09-24","description":"Machine Learning Engineer\nWashington, DC (Hybrid)\n
About the Role:\n
We are seeking a highly skilled Machine Learning Engineer to join our core AI team. In this role, you will focus on deploying, maintaining, and monitoring the AI/ML systems that power our platform. You will work closely with data scientists, data engineers, and product teams to ensure scalable, reliable, and production-grade AI solutions. You’ll play a critical role in operationalizing large language models (LLMs) and other ML systems, ensuring they run efficiently, securely, and with robust monitoring in place.\n
Key Responsibilities:\n

Design, implement, and maintain ML deployment pipelines for scalable production systems.
Operationalize large language models (LLMs) and other AI/ML models, ensuring high availability and reliability.
Build robust model monitoring, logging, and alerting systems to track performance and detect drift.
Partner with data scientists to transition models from research/prototype into production-ready deployments.
Develop CI/CD pipelines for ML workflows, integrating testing, validation, and automated deployment.
Optimize runtime performance of ML models across cloud platforms (AWS, GCP, Azure) and distributed systems.
Apply containerization and orchestration (Docker, Kubernetes) to enable reproducible, scalable systems.
Collaborate with cross-functional teams to ensure ML systems align with platform goals and business requirements.

\nQualifications:\n

5+ years of experience as a Machine Learning Engineer, MLOps Engineer, or similar role.
Proven experience deploying and maintaining machine learning models in production at scale.
Hands-on experience with ML lifecycle tooling (MLflow, Kubeflow, SageMaker, Vertex AI, or similar).
Strong proficiency in Python; familiarity with ML frameworks such as PyTorch or TensorFlow.
Deep knowledge of containerization (Docker) and orchestration (Kubernetes) for production ML systems.
Expertise with cloud platforms (AWS, GCP, Azure) for ML deployment and scaling.
Strong understanding of MLOps best practices, monitoring, and automation.
Excellent problem-solving skills, with an emphasis on building reliable, scalable systems.
Strong communication and collaboration skills across technical and non-technical teams.

","hiringOrganization":{"@type":"Organization","name":"AI Sqaured","sameAs":"https://squared.ai/"},"jobLocation":{"@type":"Place","address":{"@type":"PostalAddress","addressLocality":"Washington, DC","addressCountry":"United States","addressRegion":"North America"}}}},{"@type":"ListItem","position":9,"item":{"@type":"JobPosting","title":"Specialist Machine Learning Engineer","datePosted":"2025-09-24","description":"

Specialist Machine Learning Engineer

\n\n

It starts with YES!   

\n\n

At Optus, we are fuelled by optimism, unwavering customer focus, and a team of amazing people. And that’s where we come in…. “the amazing people” part! We don’t sit back and wait for the future to happen, we are out there crafting our own path through new technology, innovation, and investment. We are truly a challenger brand, with challenger spirit.

\n\n

Step into the thrilling world of AI and ML as a Specialist Machine Learning Engineer, where you'll be at the forefront of innovation, leading cutting-edge projects that shape the future. This role offers a unique opportunity to collaborate with top-tier professionals, push the boundaries of technology, and tackle complex challenges in a dynamic and rapidly evolving landscape. You'll have the chance to design and implement impactful solutions, utilizing the latest tools and techniques in an environment that champions growth, creativity, and staying ahead of industry trends. If you're eager to make a significant impact and be part of something transformative, this is the role for you

\n\n

Your day in the life as a Specialist Machine Learning Engineer

\n\n

Prepare and analyse data to align with data science and machine learning objectives, ensuring alignment with user stories
Develop applications using Spark in Scala, Python, or R, while maintaining adherence to best practices
Contribute to the enhancement of our technology stack by designing new AI/ML capabilities
Adhere to AI & ML Chapter Standards, including Test-Driven Development, coding standards, and DevOps code promotion practices
Assist in configuring and building scalable and efficient AI/ML solutions
Work collaboratively with cross-functional teams to integrate machine learning models into broader systems or applications
Participate in code reviews and foster team growth by sharing knowledge and best practices

\n\n

Experience Required

\n\n

2-3 years of experience in similar type of role or software engineering / development. Ideally within the AI / ML field
Bachelor’s degree in Data Science, Computer Science, Engineering, or a related field (completed or in progress)
Strong understanding of data engineering principles and best practices
Experience or a demonstrated passion for machine learning algorithms and frameworks like TensorFlow or PyTorch
Proficient in programming languages such as Scala, Python, and R, with additional knowledge of SQL being advantageous
Exceptional problem-solving abilities paired with a strong analytical mindset
Excellent communication skills, able to engage effectively with both technical and non-technical audiences
A collaborative team player who is eager to learn and contribute to team knowledge.
Familiarity with cloud platforms such as AWS, Google Cloud, or Azure
Understanding and experience with version control systems like Git

\n\n

The good stuff …

\n\n

3 days in the office, 2 days remote – with flexible hours to suit! 
Inclusive carer neutral paid Parental Leave of up to 16 weeks.
All Optus employees have access to resources, webinars and support via the ‘Parents at Work portal’ 
Own your own growth by accessing an extensive online and facilitator led learning catalogue – even earn a MBA micro-credential via OptusU (University) 
Connect at work through one of our employee-led volunteer groups: Culture Connect, Elevate Women, Disability Network, Express Yourself (LGBTQIA+), United Veterans and Yarn Network 
Vibrant campus life, variety of facilities including restaurants, cafes, gymnasium, GP, and post office

\n\n\n

At Optus, we have an ambitious goal to be Australia’s most loved everyday brand. Curious about our culture? Go behind the scenes with our people by searching #OptusLife on LinkedIn. 

\n\n

Intrigued but don't tick every box? We are building our AI capabilities and value diverse perspectives. If you're driven to join us on this journey, apply now - your passion matters more than a perfect match. 

\n\n

At Optus, we are strengthened by others and that means valuing diversity and saying ‘yes’ to embracing individual differences. We are committed to ensuring that our application process provides an equal employment opportunity to all job seekers, including individuals from diverse gender, cultural and linguistic backgrounds, individuals with a disability, individuals identifying as being part of the LGBTQIA+ community, individuals who may have served in the armed forces or who identify as Aboriginal and/or Torres Strait Islander. If you require any adjustments or accessibility support to participate fairly and equitably in the recruitment process, please email AccessibleRecruitment@optus.com.au along with your preferred method of contact and we will be in touch. 

\n\n

For more information on Diversity, Inclusion & Belonging at Optus, please visit https://www.optus.com.au/about/inclusion-diversity.

","hiringOrganization":{"@type":"Organization","name":"Singtel","sameAs":"https://www.singtel.com/"},"jobLocation":{"@type":"Place","address":{"@type":"PostalAddress","addressLocality":"Macquarie Park, Australia","addressCountry":"Australia","addressRegion":"Asia/Pacific"}}}},{"@type":"ListItem","position":10,"item":{"@type":"JobPosting","title":"Senior Machine Learning Engineer - Sentry Tower","datePosted":"2025-09-23","description":"

Anduril Industries is a defense technology company with a mission to transform U.S. and allied military capabilities with advanced technology. By bringing the expertise, technology, and business model of the 21st century’s most innovative companies to the defense industry, Anduril is changing how military systems are designed, built and sold. Anduril’s family of systems is powered by Lattice OS, an AI-powered operating system that turns thousands of data streams into a realtime, 3D command and control center. As the world enters an era of strategic competition, Anduril is committed to bringing cutting-edge autonomy, AI, computer vision, sensor fusion, and networking technology to the military in months, not years.

About The Team

The Counter Intrusion MSE team develops systems that provide force protection capabilities, monitoring the perimeter of secure areas, land or sea, for approaching people, vehicles, and vessels. We live in a world where security officers are increasingly overwhelmed by sensor data feeds. Our products leverage advanced sensor fusion and autonomy to seamlessly render activity in the environment to Lattice's common operating picture. This relieves operators of our system from a ton of burden and allows our customers to get more done with fewer personnel. Increasingly, Counter Intrusion MLEs are working on projects to bring customers' existing legacy security systems into the Lattice ecosystem. Key to this effort is building scalable software solutions so that we can service many customers without requiring bespoke software for each one. The Counter Intrusion team is responsible for the development, testing, deployment, and sustainment of our family of systems. We work closely with other teams from product, engineering, sales, logistics, operations, and mission success.

About The Role

We are looking for a Machine Learning Engineer to apply the latest research to solve our toughest problems. This role will be responsible for owning the whole machine learning stack for the Counter Intrusion team. You will design and train multi-sensor object detection models for perception on edge compute devices that push the boundaries of what's possible with our sensors. You will develop learning algorithms to optimize the behavior of autonomous systems. You will also be responsible for the end-to-end design, implementation, and performance of the ML stack, including the infrastructure for data collection and training. Your work will directly impact Anduril's ability to deliver cutting-edge defense technology, with the opportunity to identify and develop novel ML applications across our product portfolio.

Responsibilities

Propose and prototype innovative solutions to solve real-world problems, leveraging the latest state-of-the-art techniques in the field
Develop and maintain core ML pipelines
Train and deploy deep learning models for real-time applications
Collaborate cross-functionally with camera, systems and labeling teams
Curate datasets for evaluating performance and comparing performance trends over time
Provide technical mentorship to other junior ML engineers

Required Qualifications

MS or PhD in Machine Learning, Robotics or Computer Science, with emphasis on Computer Vision
BS in Computer Science, Machine Learning, Electrical Engineering, or related field
6+ years of experience developing, benchmarking and optimizing ML algorithms on large-scale datasets
Strong Deep Learning and CV background
Proficiency in C++ development in a Linux environment
Experience with Python development and deep learning frameworks such as PyTorch, JAX and TensorFlow
Experience deploying models with TensorRT and ONNX
Optimize on-device inference and vision kernels across CPU/GPU/NPU
Track record of developing and deploying CV models from R&D to production
Experience writing and maintaining automated continuous integration tests
Knowledge of system profiling and tuning for latency, memory and power efficiency
Ability to conduct experiments, ablation studies and create highly detailed reports
Eligible to obtain and maintain a U.S. Secret security clearance

Preferred Qualifications

Experience in one or more of the following:

Object Detection, Object Tracking, Instance Segmentation, Semantic Segmentation, Semantic Change Detection, Depth Estimation, Model Pruning and Compression

Experience in one or more of the following:

Visual Odometry, SLAM, Multi-view Geometry, Camera Models, RGB-D and LIDAR Sensor Fusion, Optical Flow

Experience troubleshooting and analyzing remotely deployed software systems
+1 year of experience in a technical leadership role

US Salary Range$168,000—$250,000 USD\n

The salary range for this role is an estimate based on a wide range of compensation factors, inclusive of base salary only. Actual salary offer may vary based on (but not limited to) work experience, education and/or training, critical skills, and/or business considerations. Highly competitive equity grants are included in the majority of full time offers; and are considered part of Anduril's total compensation package. Additionally, Anduril offers top-tier benefits for full-time employees, including:

Platinum Healthcare Benefits: For U.S. roles, we offer comprehensive medical, dental, and vision plans at little to no cost to you.\n\n
Basic Life/AD&D and long-term disability insurance 100% covered by Anduril, plus the option to purchase additional life insurance for you and your dependents.
Extremely generous company holiday calendar including a holiday hiatus in December, and highly competitive PTO plans.
16 weeks of paid Caregiver & Wellness Leave to care for a family member, bond with your baby, or tend to your own medical condition.
Family Planning & Parenting Support: Fertility (eg, IVF, preservation), adoption, and gestational carrier coverage with additional benefits and resources to provide support from planning to parenting.
Mental Health Resources: We provide free mental health resources 24/7 including therapy, life coaching, and more. Additional work-life services, such as free legal and financial support, available to you as well.
A professional development stipend is available to all Andurilians.
Company-funded commuter benefits available based on your region.
Relocation assistance (depending on role eligibility).
401(k) retirement savings plan - both a traditional and Roth 401(k). (US roles only)
For UK roles, Private Medical Insurance (PMI): Anduril will cover the full cost of the insurance premium for an employee and dependents.
For AUS roles, Private health plan through Bupa: Coverage is fully subsidized by Anduril.

The recruiter assigned to this role can share more information about the specific compensation and benefit details associated with this role during the hiring process.

Anduril is an equal-opportunity employer committed to creating a diverse and inclusive workplace. The Anduril team is made up of incredibly talented and unique individuals, who together are disrupting industry norms by creating new paths towards the future of defense technology. All qualified applicants will be treated with respect and receive equal consideration for employment without regard to race, color, creed, religion, sex, gender identity, sexual orientation, national origin, disability, uniform service, Veteran status, age, or any other protected characteristic per federal, state, or local law, including those with a criminal history, in a manner consistent with the requirements of applicable state and local laws, including the CA Fair Chance Initiative for Hiring Ordinance. We actively encourage members of recognized minorities, women, Veterans, and those with disabilities to apply, and we work to create a welcoming and supportive environment for all applicants throughout the interview process. If you are someone passionate about working on problems that have a real-world impact, we'd love to hear from you!

To view Anduril's candidate data privacy policy, please visit https://anduril.com/applicant-privacy-notice/.

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Our Mission: To Eliminate Every Barrier To Mental Health.

At Spring Health, we’re on a mission to revolutionize mental healthcare by removing every barrier that prevents people from getting the help they need, when they need it. Our clinically validated technology, Precision Mental Healthcare, empowers us to deliver the right care at the right time—whether it’s therapy, coaching, medication, or beyond—tailored to each individual’s needs.

We proudly partner with over 450 companies, from startups to multinational Fortune 500 corporations, as a leading provider of mental health service, providing care for 10 million people. Our clients include brands you use and know like Microsoft, Target, and Delta Airlines, all of whom trust us to deliver best-in-class outcomes for their employees globally. With our innovative platform, we’ve been able to generate a net positive ROI for employers and we are the only company in our category to earn external validation of net savings for customers.

We have raised capital from prominent investors including Generation Investment, Kinnevik, Tiger Global, Northzone, RRE Ventures, and many more. Thanks to their partnership and our latest Series E Funding, our current valuation has reached $3.3 billion. We’re just getting started—join us on our journey to make mental healthcare accessible to everyone, everywhere.

As a Machine Learning Engineer on our AI and ML Infrastructure team, you'll be a key player in our mission to accelerate improvements that remove barriers to mental health. Your role is to build the foundational LLM infrastructure, tools, and automated systems that empower all of our product teams to deliver features faster, safer, and more reliably.

This is a hands-on role where you will build the \"paved road\" for AI development at Spring Health. You will tackle complex technical challenges by turning clear solutions into well-defined technical plans for LLM Ops and shared LLM components. You will not only build for today's needs but also lay the groundwork for future capabilities.

Please note that this is a hybrid role based in San Francisco, with an expectation to be in office 2-3 days a week. Our office is located at 2 Embarcadero Ctr.

What You’Ll Do

Build Foundational LLM Tooling: Design, build, and maintain the core components of our LLM infrastructure. This includes operationalizing tools like LangSmith for observability, creating shared patterns for using orchestration frameworks, and developing reusable libraries that make our feature teams more productive.
Develop Advanced AI Capabilities: Build the platform to support sophisticated LLM use cases. You will help deploy and build the pipelines for a vector database to enable Retrieval-Augmented Generation (RAG) across multiple product teams.
Pioneer Future-State Infrastructure: Contribute to proofs-of-concept and the architectural groundwork for future innovations.
Ensure Platform Excellence & Scalability: Consistently add logging, monitoring, and alerting to the platform services you build. Your team is accountable to ensure the platform is stable, performant, and cost-effective for its internal users.
Partner with Feature Teams: Work closely with engineers across the organization to understand their needs and challenges. You will act as a consultant and enabler, providing the tools and patterns that unblock their work and accelerate their AI roadmaps.

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What Success Looks Like:

Platform Adoption & Developer Enablement

Accelerate onboarding by cutting the time it takes for new engineers to make their first successful call to the platform.
Improve developer satisfaction and drive adoption of new platform features each quarter.

Operational Excellence & Reliability

Meet or exceed SLOs for core services, such as uptime and latency, and lower the average time to resolve incidents (MTTR).
Increase automation by improving test coverage and reducing repetitive support questions through better documentation.

Roadmap Delivery & Project Execution

Deliver committed roadmap items on schedule each sprint or quarter.
Produce high-quality work, from clear technical designs to clean, maintainable code.

Team & Cross-functional Collaboration

Earn positive feedback from internal platform users and stakeholders.
Elevate the team by improving internal processes and sharing knowledge through mentorship and documentation.

What You’Ll Bring

Proven Experience: Demonstrated experience building and delivering production-grade software, with significant, hands-on experience in LLM or Generative AI engineering.
A Platform Builder's Mindset: You think in terms of abstractions, reusability, and creating leverage for other engineers. You have experience building internal tools, libraries, or platforms and understand the importance of clear documentation and API design for your internal customers.
Technical Proficiency: Strong proficiency in Python and familiarity with the modern AI/ML stack, including cloud services (AWS, GCP, or Azure) and CI/CD pipelines. You are adept at making smart, practical tradeoffs to meet goals.
LLM & Generative AI Expertise: Hands-on experience building or working with key components of the modern LLM stack. Direct experience with orchestration frameworks (e.g., LangChain, LangGraph), observability tools (e.g., LangSmith), and the infrastructure for Retrieval-Augmented Generation (RAG) like vector databases is a significant plus.
Pragmatic Problem-Solving: The ability to operate at a feature scope, breaking down clearly defined solutions into smaller, manageable tasks. You can proactively identify and mitigate risks and think through what might be coming in the next sprint.
Resilience and Drive: A high degree of grit and comfort with the ambiguity that comes with a fast-paced, high-growth environment. You take ownership, see challenges as opportunities, and are resourceful in finding solutions.
Education: A Bachelor's degree in a technical field or equivalent practical experience. We value the diverse perspectives that different backgrounds bring to our team.
Security and Privacy Awareness: A deep understanding of the importance of handling sensitive data.

The target base salary range for this position is $120,000 - 165,275, and is part of a competitive total rewards package including stock options and benefits. Individual pay may vary from the target range and is determined by a number of factors including experience, location, internal pay equity, and other relevant business considerations. We review all employee pay and compensation programs annually using Radford Global Compensation Database at minimum to ensure competitive and fair pay.

Benefits Provided By Spring Health:

Note: We have even more benefits than listed here and below, your recruiter will provide more in-depth information as you continue in the interview process. Benefits are subject to individual plan requirements and eligibility criteria.

Health, Dental, Vision benefits start on your first day at Spring. You and your dependents also receive access to One Medical accounts HSA and FSA plans are also available, with Spring contributing up to $1K for HSAs, depending on your plan type.
Employer sponsored 401(k) match of up to 2% for retirement planning
A yearly allotment of no cost visits to the Spring Health network of therapists, coaches, and medication management providers for you and your dependents.
We offer competitive paid time off policies including vacation, sick leave and company holidays.
At 6 months tenure with Spring, we offer parental leave of 18 weeks for birthing parents and 16 weeks for non-birthing parents.
Access to Noom, a weight management program—based in psychology, that’s tailored to your unique needs and goals.
Access to fertility care support through Carrot, in addition to $4,000 reimbursement for related fertility expenses.
Access to Wellhub, which connects employees to the best options for fitness, mindfulness, nutrition, and sleep in one subscription
Access to BrightHorizons, which provides sponsored child care, back-up care, and elder care
Up to $1,000 Professional Development Reimbursement a year.
$200 per year donation matching to support your favorite causes.

Not sure if you meet every requirement? Research shows that women and people from historically underrepresented communities often hesitate to apply for roles unless they meet every qualification compared to other similarly-qualified candidates. At Spring Health, we are committed to fostering a workplace where everyone feels valued, empowered, and supported to Thrive. If this role excites you, we encourage you to apply.

Ready to do the most impactful work of your life? Learn more about our values, what it’s like to work here, and how hypergrowth meets impact at Spring Health: Our Values

Our privacy policy: https://springhealth.com/privacy-policy/

Spring Health is proud to be an equal opportunity employer. We do not discriminate in hiring or any employment decision based on race, color, religion, national origin, age, sex, marital status, ancestry, disability, genetic information, veteran status, gender identity or expression, sexual orientation, pregnancy, or other applicable legally protected characteristic. We also consider qualified applicants regardless of criminal histories, consistent with applicable legal requirements. Spring Health is also committed to providing reasonable accommodations for qualified individuals with disabilities and disabled veterans. If you have a disability or special need that requires accommodation, please let us know.

","hiringOrganization":{"@type":"Organization","name":"Spring Health","sameAs":"https://www.springhealth.com/"},"jobLocation":{"@type":"Place","address":{"@type":"PostalAddress","addressLocality":"San Francisco, CA (Hybrid)","addressCountry":"United States","addressRegion":"North America"}}}},{"@type":"ListItem","position":12,"item":{"@type":"JobPosting","title":"Senior Machine Learning Engineer","datePosted":"2025-09-23","description":"

Senior Machine Learning Engineers at Thoughtworks build, maintain and test the architecture and infrastructure for managing machine learning applications. They are involved in supporting and contributing to the design of the end-to-end applications and products. They are responsible for building core capabilities including technical and functional machine learning systems and applications, being the anchor for functional streams of work and are accountable for timely delivery.

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As a senior machine learning engineer, you will work on the latest tools, frameworks and offerings while also being involved in enabling credible and collaborative problem solving to execute on a strategy.

\n\n

Job Responsibilities

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You will contribute to design and drive the development of robust scalable architectures and infrastructure for deploying and managing machine learning (ML) applications, ensuring high availability, performance and security
You will collaborate with data scientists and engineers to translate business needs into effective and efficient ML systems and applications
You will own the development and maintenance of core functionalities within ML applications, including ML pipelines, model training and deployment, and monitoring and evaluation
You will drive the functional stream of work by providing technical expertise, handling team discussions and ensuring timely delivery of assigned tasks
You will stay ahead of the curve by actively exploring and implementing the latest tools, frameworks and offerings in the ML landscape
You will facilitate collaborative problem solving within the team by actively listening, communicating effectively and mentoring other engineers
You will contribute to the development and execution of the team's overall ML strategy, aligning technical capabilities with business objectives
You will proactively identify and address challenges related to ML systems and applications, proposing solutions and implementing improvements

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Job Qualifications

\n\n

Technical Skills

\n\n

You have experience in writing clean, maintainable and testable code, demonstrating attention to refactoring and readability of the code
You are proficient in scripting languages such as Python or Shell for automation and task streamlining
You have knowledge of distributed systems and scalable architectures to handle large-scale ML applications
You have experience with building, deploying, and maintaining ML systems using relevant ML techniques and platforms, i.e.: Scikit-learn, Tensorflow, MLFlow, Kubeflow, Pytorch
You have experience with building, deploying and maintaining ML systems and experience with application of MLOps principles and CI/CD to ML
You have experience in machine learning engineering and data science, are familiar with key ML concepts, algorithms and frameworks, and understand ML model lifecycles
You have experience with designing and operating the infrastructure required to run different types of ML training and serving workloads, i.e.: on-premise vs. cloud infrastructure, infrastructure as code, monitoring, etc.
You have hands-on experience with on-premise and cloud services for building and deploying ML pipelines, i.e.: Azure, AWS, GCP or Databricks and associated ML managed services

\n\n

Professional Skills

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You understand the importance of stakeholder management and can easily liaise between clients and other key stakeholders throughout projects, ensuring buy-in and gaining trust along the way
You are resilient in ambiguous situations and can adapt your role to approach challenges from multiple perspectives
You don’t shy away from risks or conflicts, instead you take them on and skillfully manage them
You are eager to coach, mentor and motivate others and you aspire to influence teammates to take positive action and accountability for their work
You enjoy influencing others and always advocate for technical excellence while being open to change when needed

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Other Things To Know

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Learning & Development

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There is no one-size-fits-all career path at Thoughtworks: however you want to develop your career is entirely up to you. But we also balance autonomy with the strength of our cultivation culture. This means your career is supported by interactive tools, numerous development programs and teammates who want to help you grow. We see value in helping each other be our best and that extends to empowering our employees in their career journeys.

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Travel

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While we’ve traditionally been a traveling consultancy, we have adopted a hybrid working model with the majority of work being completed remotely from either home or local Thoughtworks offices. However, business travel to client locations should be expected when required by Thoughtworks or our clients’ needs.

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Company Policies

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We are an equal opportunity employer and all qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity or expression, pregnancy, age, national origin, disability status, genetic information, protected veteran status, or any other characteristic protected by law.

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About Thoughtworks

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Thoughtworks is a global technology consultancy that integrates strategy, design and engineering to drive digital innovation. For 30+ years, our clients have trusted our autonomous teams to build solutions that look past the obvious. Here, computer science grads come together with seasoned technologists, self-taught developers, midlife career changers and more to learn from and challenge each other. Career journeys flourish with the strength of our cultivation culture, which has won numerous awards around the world.

Join Thoughtworks and thrive. Together, our extra curiosity, innovation, passion and dedication overcomes ordinary.

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#Li-Remote

Salary

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Benefits: https://www.thoughtworks.com/en-us/careers/benefits

The annual salary range posted is subject to many factors and may vary depending on experience, geographic location, job responsibilities, performance, skills and/or training.

\nSalary$143,800—$215,700 USD

See here our AI policy.

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\n\n

Job Responsibilities

\n\n

You will contribute to design and drive the development of robust scalable architectures and infrastructure for deploying and managing machine learning (ML) applications, ensuring high availability, performance and security
You will collaborate with data scientists and engineers to translate business needs into effective and efficient ML systems and applications
You will own the development and maintenance of core functionalities within ML applications, including ML pipelines, model training and deployment, and monitoring and evaluation
You will drive the functional stream of work by providing technical expertise, handling team discussions and ensuring timely delivery of assigned tasks
You will stay ahead of the curve by actively exploring and implementing the latest tools, frameworks and offerings in the ML landscape
You will facilitate collaborative problem solving within the team by actively listening, communicating effectively and mentoring other engineers
You will contribute to the development and execution of the team's overall ML strategy, aligning technical capabilities with business objectives
You will proactively identify and address challenges related to ML systems and applications, proposing solutions and implementing improvements

\n\n

Job Qualifications

\n\n

Technical Skills

\n\n

You have experience in writing clean, maintainable and testable code, demonstrating attention to refactoring and readability of the code
You are proficient in scripting languages such as Python or Shell for automation and task streamlining
You have knowledge of distributed systems and scalable architectures to handle large-scale ML applications
You have experience with building, deploying, and maintaining ML systems using relevant ML techniques and platforms, i.e.: Scikit-learn, Tensorflow, MLFlow, Kubeflow, Pytorch
You have experience with building, deploying and maintaining ML systems and experience with application of MLOps principles and CI/CD to ML
You have experience in machine learning engineering and data science, are familiar with key ML concepts, algorithms and frameworks, and understand ML model lifecycles
You have experience with designing and operating the infrastructure required to run different types of ML training and serving workloads, i.e.: on-premise vs. cloud infrastructure, infrastructure as code, monitoring, etc.
You have hands-on experience with on-premise and cloud services for building and deploying ML pipelines, i.e.: Azure, AWS, GCP or Databricks and associated ML managed services

\n\n

Professional Skills

\n\n

You understand the importance of stakeholder management and can easily liaise between clients and other key stakeholders throughout projects, ensuring buy-in and gaining trust along the way
You are resilient in ambiguous situations and can adapt your role to approach challenges from multiple perspectives
You don’t shy away from risks or conflicts, instead you take them on and skillfully manage them
You are eager to coach, mentor and motivate others and you aspire to influence teammates to take positive action and accountability for their work
You enjoy influencing others and always advocate for technical excellence while being open to change when needed

\n\n\n

Other Things To Know

\n\n

Learning & Development

\n\n

Travel

\n\n

Company Policies

\n\n

\n\n\n

About Thoughtworks

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#Li-Remote

See here our AI policy.

","hiringOrganization":{"@type":"Organization","name":"Thoughtworks","sameAs":"https://www.thoughtworks.com/"},"jobLocation":{"@type":"Place","address":{"@type":"PostalAddress","addressLocality":"Toronto","addressCountry":"Canada","addressRegion":"North America"}}}},{"@type":"ListItem","position":14,"item":{"@type":"JobPosting","title":"Machine Learning Engineer","datePosted":"2025-09-23","description":"

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.

Led by former Meta AI Research engineers, our team has consistently anticipated how AI can revolutionize healthcare delivery. Our 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.

Engineering At Nabla

Engineering at Nabla is lean, fast-moving, and deeply technical. Our teams span machine learning, native desktop applications, and platform infrastructure to deliver AI into clinical settings reliably and at scale.

Your Team

The Engineering team currently comprises 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.

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

What You'Ll Do

As a machine learning engineer, you will leverage the latest advances in machine learning to build the \"Copilot\" of healthcare. You will be deeply involved in the ML roadmap, from definition to delivery.

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

Propose experiments, model architectures & data labeling strategies to improve our speech to text, note generation and normalization systems.
Implement them and train models
Roll them out on our platform by working closely with product teams
Measure their performance in the real world to improve them over time

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.

Your Dna

You have strong foundations in machine learning
You’ve trained neural networks for real-world use cases
You write clean Python code
You communicate clearly in English
Broader software engineering experience (infrastructure, front-end, etc) is a plus

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.

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!

Our Values At Nabla

Joining Nabla means being part of a team that shares a commitment to excellence, humility, growth, and inclusion.

Every day is a new chance to excel

We aim for nothing less than the best and are willing to put in the effort and dedication required to exceed standards. We learn from yesterday’s failures and do better every day.

Stay Humble

There’s no place for ego in our team. Our collective success is more important than individual achievements. We see humility as wisdom — keeping focus on the bigger picture.

Feedback is a gift

We embrace feedback and foster a culture of trust and respect that helps everyone grow. We communicate openly about both achievements and challenges, and we actively involve each other in finding solutions.

Committed To Diversity

We recognize the ongoing challenge of diversity in tech. Our responsibility starts with fostering an inclusive environment where everyone feels empowered to be their authentic selves and do their best work.

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.
Nabla does not accept unsolicited CVs from recruiters or employment agencies in response to the Nabla Careers page or a Nabla social media post. Any unsolicited CVs, including those submitted directly to hiring managers, are deemed to be the property of Nabla.

","hiringOrganization":{"@type":"Organization","name":"Nabla","sameAs":"https://www.nabla.com/"},"jobLocation":{"@type":"Place","address":{"@type":"PostalAddress","addressLocality":"Paris office","addressCountry":"France","addressRegion":"Europe"}}}},{"@type":"ListItem","position":15,"item":{"@type":"JobPosting","title":"Senior Machine Learning Engineer","datePosted":"2025-09-23","description":"\n

About Prove

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As the world moves to a mobile-first economy, businesses need to modernize how they acquire, engage with and enable consumers. Prove’s phone-centric identity tokenization and passive cryptographic authentication solutions reduce friction, enhance security and privacy across all digital channels, and accelerate revenues while reducing operating expenses and fraud losses. Over 1,000 enterprise customers use Prove’s platform to process 20 billion customer requests annually across industries, including banking, lending, healthcare, gaming, crypto, e-commerce, marketplaces, and payments. For the latest updates from Prove, follow us on LinkedIn.

Prove is driving the future of digital identity. We are looking for Provers who know how to make an impact. We’re talking self-starting professionals who thrive in a fast-paced environment, process information quickly, and make intelligent decisions. The work is challenging and requires not only smart but natural curiosity and tenacity. Teamwork is also important to us – we work together and play together.

Prove has big plans, and we’re excited about the future. If this sounds like the place for you – come join our team!

Title: Senior Machine Learning Engineer
Department: Data Engineering - Engineering
Reports To: Senior Manager, Data Intelligence
FLSA Status: Exempt
Location: USA

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Job Summary

We are looking for a Senior Machine Learning Engineer to join our team and play a critical role in bridging data science and software engineering. In this role, you will partner with data scientists to take models from prototype to production, and with software engineers to build APIs and services that are performant, reliable, and scalable. You’ll be responsible for ensuring that machine learning systems are production-ready, monitored, and continuously improved.

This position is ideal for someone who thrives at the intersection of machine learning, software engineering, and MLOps.

Key Responsibilities

Model Deployment & Integration

Collaborate with data scientists to transform research models into production-ready services.
Design, build, and maintain APIs and microservices to serve ML models at scale.
Ensure smooth integration of ML solutions into core products and platforms.

Performance & Reliability

Optimize inference performance, latency, and scalability.
Build monitoring, logging, and alerting systems to track model performance and data drift.
Implement retraining pipelines and automated workflows for continuous improvement.

Engineering & MLOps

Develop CI/CD pipelines for machine learning workflows.
Use modern DevOps/MLOps practices to ensure reproducibility and reliability.
Partner with software engineers to design robust data and compute infrastructure.

Collaboration & Leadership

Work closely with cross-functional teams to align model capabilities with business needs.
Mentor junior engineers and contribute to best practices in ML engineering.
Advocate for scalable, sustainable ML deployment strategies across the organization.

Qualifications

Education & Experience

5-7+ years of professional experience in ML engineering, software engineering, or related roles.
Bachelor’s Master’s in Computer Science, Engineering, or related field (required).
Master’s in Computer Science, Engineering, or related field, or equivalent experience (preferred).

Technical Skills

Strong programming skills in Python (and experience with libraries such as scikit-learn, TensorFlow, or PyTorch), Java, and/or Go.
Hands-on experience building APIs and services (e.g., FastAPI, Flask, gRPC).
Expertise with containerization & orchestration (Docker, Kubernetes).
Familiarity with CI/CD pipelines and modern MLOps tools (MLflow, Airflow, Kubeflow, SageMaker, or similar).
Strong understanding of cloud platforms (AWS).
Solid background in data pipelines, distributed systems, and performance optimization.

Soft Skills

Strong collaboration skills with both data scientists and software engineers.
Ability to balance technical rigor with pragmatic delivery.
Excellent communication and problem-solving abilities.

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What We Offer

Competitive compensation and benefits.
Opportunities to shape end-to-end ML systems in production.
A collaborative, high-impact environment where ML solutions directly drive business outcomes.

This position description should not be considered the final description of the position. The position description is not intended to be an all-inclusive list of duties and standards of the positions. It should be assumed that we would, to some extent, structure responsibilities in accordance with the successful candidate’s capabilities and changing business conditions. Incumbents will follow any other instructions, and perform any other related duties, as assigned by their supervisor.

The anticipated salary range for this role is $185,000 - $195,000 plus variable commission / company bonus. Offered salary will be determined by the applicant’s education, experience, knowledge, skills, geo-location and abilities, as well as internal equity and alignment with market data.

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Benefits & Perks for FTE Provers:

Competitive salaries & Bonus Plan (for eligible roles) and Equity Plan
Modern Health for financial, mental, and physical wellness
401(k) Retirement Plan & Match (US Offices) and Local Country Pension (International Offices)
Unlimited Vacation and Flexible hours
Comprehensive medical benefits for you and your family ❤️
Emotional & Physical Wellness – Access to wellness services (EAP & Prove Well-Being Reimbursement)
Bottomless snacks & beverages for certain office locations
Daily GrubHub stipend for lunch if coming into the office (US Offices)
A great place to work and connect with other talented Provers like yourself!

\n\n\n

Don’t meet every single requirement? Studies have shown that women and people of color are less likely to apply to jobs unless they meet every single qualification. At Prove we are dedicated to building a diverse, inclusive and authentic workplace, so if you’re excited about this role but your past experience doesn’t align perfectly with every qualification in the job description, we encourage you to apply anyways. You may be just the right candidate for this or other roles.

Equal Opportunity Employment:

Prove is an equal opportunity employer committed to providing equal employment opportunity for all people regardless of race, color, religion, gender or sexual orientation, age, marital status, national origin, citizenship status, disability, veteran status or other personal characteristics

Privacy & Data Protection:

When you are applying for a job at Prove, we collect and use your personal information in the job application process. To understand more about how Prove uses your personal information, please see our Recruitment Privacy Policy on our website.

","hiringOrganization":{"@type":"Organization","name":"Prove","sameAs":"https://www.prove.com/"},"jobLocation":{"@type":"Place","address":{"@type":"PostalAddress","addressLocality":"United States","addressCountry":"United States","addressRegion":"North America"}}}},{"@type":"ListItem","position":16,"item":{"@type":"JobPosting","title":"Product Machine Learning Engineer","datePosted":"2025-09-23","description":"🚀 Join Our Data Products and Machine Learning Development Remote Startup! 🚀
Mutt Data is a dynamic startup committed to crafting innovative systems using cutting-edge Big Data and Machine Learning technologies.
We’re looking for a Machine Learning Engineer to help take our expertise to the next level. If you consider yourself a data nerd like us, we’d love to connect! 🐶🚀\n

🚀 What We Do

Leveraging our expertise, we build modern Machine Learning systems for demand planning and budget forecasting.
Developing scalable data infrastructures, we enhance high-level decision-making, tailored to each client.
Offering comprehensive Data Engineering and custom AI solutions, we optimize cloud-based systems.
Using Generative AI, we help e-commerce platforms and retailers create higher-quality ads, faster.
Building deep learning models, we enhance visual recognition and automation for various industries, improving product categorization, quality control, and information retrieval.
Developing recommendation models, we personalize user experiences in e-commerce, streaming, and digital platforms, driving engagement and conversions.

🌟 Our Partnerships

Amazon Web Services
Astronomer
Databricks

🌟 Our Values

📊 We are Data Nerds
🤗 We are Open Team Players
🚀 We Take Ownership
🌟 We Have a Positive Mindset

our

blog post

Responsibilities 🤓

Develop and optimize ML models, ensuring scalability, monitoring, and integration with MLOps best practices.
Implement client requirements, from exploratory data analysis (EDA) to feature engineering and model lifecycle management.
Build ML Proof of Concepts (POCs) to validate and refine solutions.
Optimize models for performance, latency, memory, and throughput.
Apply statistical analysis techniques and develop regression models.
Design and maintain feature stores and data pipelines for ML workflows.
Research and implement emerging ML/AI techniques to enhance solutions.
Collaborate with stakeholders to align technical solutions with business needs.

Required Skills

Experience implementing ML-based systems, including model lifecycle management, monitoring, and MLOps pipeline setup.
Strong proficiency in Python (Pandas, Numpy, Jupyter, Scikit-Learn, XGBoost, Plotly).Knowledge of SQL
Experience with cloud platforms (AWS, GCP, Azure).

Nice To Have Skills 😉

Experience with ML workflows (Airflow, MLflow, H2OAI, Databricks, or similar).
Background in modern LLM technologies.
Understanding of Deep Learning frameworks (Keras, PyTorch, TensorFlow).Basic knowledge of Docker.

🎁 Perks

🌍 Remote-first culture – work from anywhere!
🚀 In-Company English Lessons.
💪 Wellhub or sports club stipend to stay active
🚀 AWS & Databricks certifications fully covered (reward salary increase for AWS certifications!)
🍕 Food credits via Pedidos Ya – because great work deserves great food.
🎂 Birthday off + an extra vacation week (Mutt Week! 🏖️)
🤝 Referral bonuses – help us grow the team & get rewarded!
✈️🏝️ Annual Mutters' Trip – an unforgettable getaway with the team!

","hiringOrganization":{"@type":"Organization","name":"Mutt Data","sameAs":"https://muttdata.ai/"},"jobLocation":{"@type":"Place","address":{"@type":"PostalAddress","addressLocality":"Argentina","addressCountry":"Argentina","addressRegion":"South America"}}}},{"@type":"ListItem","position":17,"item":{"@type":"JobPosting","title":"Staff Machine Learning Engineer, Ads Delivery","datePosted":"2025-09-23","description":"

About Pinterest:

\n\n

What You’Ll Do:

Build and improve backend systems and statistical models that underlay the marketplace to maximize value for Pinners, Partners and Pinterest.
Define and implement experiments to understand long term Marketplace effects.
Develop strategies to balance long and short term business objectives.
Drive multi-functional collaboration with peers and partners across the company to improve knowledge of marketplace design and operations.

\n\n

What We’Re Looking For:

MS or PhD degree in Computer Science, Statistics or related field.
6+ years of industry experience.
2+ years of experience leading projects/teams.
Strong software engineering and mathematical skills with knowledge of statistical methods.
Hands-on experience with large-scale online e-commerce systems is a plus.
Background in computational advertising is preferred, but not required.

\n\n

Relocation Statement:

This position is not eligible for relocation assistance. Visit our PinFlex page to learn more about our working model.

\n\n

In-Office Requirement Statement:

We let the type of work you do guide the collaboration style. That means we're not always working in an office, but we continue to gather for key moments of collaboration and connection.
This role will need to be in the office for in-person collaboration 1-2 times/month, and therefore needs to be in a commutable distance from one of the following offices: San Francisco, Palo Alto, Seattle.

\n\n

#Li-Hybrid

#Li-Sm4

Information regarding the culture at Pinterest and benefits available for this position can be found here.

US based applicants only$208,145—$364,254 USD

Our Commitment To Inclusion:

\nPinterest is an equal opportunity employer and makes employment decisions on the basis of merit. We want to have the best qualified people in every job. All qualified applicants will receive consideration for employment without regard to race, color, ancestry, national origin, religion or religious creed, sex (including pregnancy, childbirth, or related medical conditions), sexual orientation, gender, gender identity, gender expression, age, marital status, status as a protected veteran, physical or mental disability, medical condition, genetic information or characteristics (or those of a family member) or any other consideration made unlawful by applicable federal, state or local laws. We also consider qualified applicants regardless of criminal histories, consistent with legal requirements. If you require a medical or religious accommodation during the job application process, please complete this form for support.","hiringOrganization":{"@type":"Organization","name":"Pinterest","sameAs":"https://www.pinterest.com/"},"jobLocation":{"@type":"Place","address":{"@type":"PostalAddress","addressLocality":"San Francisco, CA, US; Palo Alto, CA, US; Seattle, WA, US","addressCountry":"United States","addressRegion":"North America"}}}},{"@type":"ListItem","position":18,"item":{"@type":"JobPosting","title":"Senior Machine Learning Engineer - Visa AI as a Service","datePosted":"2025-09-23","description":"

Company Description

Visa is a world leader in payments and technology, with over 259 billion payments transactions flowing safely between consumers, merchants, financial institutions, and government entities in more than 200 countries and territories each year. Our mission is to connect the world through the most innovative, convenient, reliable, and secure payments network, enabling individuals, businesses, and economies to thrive while driven by a common purpose – to uplift everyone, everywhere by being the best way to pay and be paid.

Make an impact with a purpose-driven industry leader. Join us today and experience Life at Visa.

Job Description

Ready to make a global impact by industrializing AI?

About The Role:

Visa AI as a Service (VAIaS) operationalizes the delivery of AI and decision intelligence to ensure their ongoing business values. Built with composable AI capabilities, privacy-enhancing computation, and cloud native platforms, VAIaS automates the updates to data, models, and applications. Combined with strong AI governance, VAIaS optimizes the performance, scalability, interpretability and reliability of AI models and services. If you want to be in the exciting payment and AI space, learn fast, and make big impacts, Visa AI as a Service is an ideal place for you!

We are looking for a talented and versatile entry-level Machine Learning Engineer to join our growing team. In this role, you will be a key contributor to the full lifecycle of our core machine learning infrastructure. You will be responsible for both building our high-performance, low-latency model inference engine and ensuring its rock-solid reliability through a best-in-class observability platform.

This is a role for a strong software and machine learning engineering generalist who is passionate about building robust, scalable systems. You will be empowered to solve complex problems, write production-grade code, and make a significant impact on the systems that power our intelligent products.

Key Responsibilities:

Design, build, and maintain the full lifecycle of our machine learning systems, from our low-latency inference engine to the observability platform that supports it.
Develop and optimize high-performance, mission-critical services using languages like Rust, Python, and Go.
Enhance the reliability and visibility of our MLOps ecosystem by building and scaling solutions for monitoring, logging, and tracing.
Collaborate closely with data scientists and ML engineers to deploy, scale, and troubleshoot machine learning models in production.
Write clean, high-quality, and well-tested code, and participate in code reviews to raise the bar for the entire team.
Diagnose and resolve performance bottlenecks and system failures in our production environment.

If you are passionate about machine learning, model inference technology, large scale low latency system and are excited about making a significant impact, we would love to hear from you.

This is a hybrid position based in Austin, TX, allowing alternating between remote and office work. Expectations are to be in-office at least three days a week, aiming for a 50% office presence based on business requirements.

Qualifications

Basic Qualifications

2 or more years of work experience with a Bachelor’s Degree or an Advanced Degree (e.g. Masters, MBA, JD, MD).

Preferred Qualifications

Strong programming proficiency in at least one of the following languages: Rust/C++/Go/Java
A strong desire to learn and a passion for building impactful, high-performance systems.
Experience with performance optimization.
Hands-on experience with containerization and orchestration technologies (e.g., Docker, Kubernetes).
Familiarity with observability tools (e.g., Prometheus, Grafana, OpenTelemetry) and cloud platforms (AWS, GCP, Azure).
Knowledge of network programming, gRPC, Protocol Buffers, or other RPC frameworks.
Experience working on large-scale distributed systems.

Additional Information

Work Hours: Varies upon the needs of the department.

Travel Requirements: This position requires travel 5-10% of the time.

Mental/Physical Requirements: This position will be performed in an office setting. The position will require the incumbent to sit and stand at a desk, communicate in person and by telephone, frequently operate standard office equipment, such as telephones and computers.

Visa is an EEO Employer. Qualified applicants will receive consideration for employment without regard to race, color, religion, sex, national origin, sexual orientation, gender identity, disability or protected veteran status. Visa will also consider for employment qualified applicants with criminal histories in a manner consistent with EEOC guidelines and applicable local law.

Visa will consider for employment qualified applicants with criminal histories in a manner consistent with applicable local law, including the requirements of Article 49 of the San Francisco Police Code.

U.S. APPLICANTS ONLY: The estimated salary range for a new hire into this position is $116,500.00 to $164,500.00 USD per year, which may include potential sales incentive payments (if applicable). Salary may vary depending on job-related factors which may include knowledge, skills, experience, and location. In addition, this position may be eligible for bonus and equity. Visa has a comprehensive benefits package for which this position may be eligible that includes Medical, Dental, Vision, 401 (k), FSA/HSA, Life Insurance, Paid Time Off, and Wellness Program.

","hiringOrganization":{"@type":"Organization","name":"Visa","sameAs":"https://visa.com"},"jobLocation":{"@type":"Place","address":{"@type":"PostalAddress","addressLocality":"Austin, TX, United States","addressCountry":"United States","addressRegion":"North America"}}}},{"@type":"ListItem","position":19,"item":{"@type":"JobPosting","title":"Senior Machine Learning Engineer - Behaviors","datePosted":"2025-09-23","description":"

On Behaviors, you'll have the opportunity to work with world-class ML engineers and research scientists to make self-driving vehicles a reality and create positive social impact. Our team works on the tech stack responsible for understanding highly complex driving scenes and generating safe, comfortable driving trajectories for our robotaxi using the latest deep neural networks. We are looking for engineers who are passionate about Level 5 autonomous driving, excited by intellectual challenges, and interested in pursuing career growth with a fast growing company.

What You’Ll Be Doing:

You will be directly responsible for training, evaluation, and deployment of our ML-based scene understanding, behavior prediction, and planning models. Day to day responsibilities include:

Designing and executing high value experiments based on collaborative input from other machine learning engineers
Prototyping and implementing continuously improving metrics to evaluate the performance of our behavioral models across many desired scenarios and robotaxi capabilities
Timely release of major model updates, including analysis of both off-line and on-road evaluation data
Staying up to date with the latest trends in our fast moving industry, and proposing new architectures and network designs based on published literature
Maintaining a high quality training and evaluation code-base, including portions of our training stack dedicated to dataset generation and evaluation

What We’Re Looking For:

In-depth understanding of common Machine Learning and Deep Learning algorithms
Experience designing, training, and analyzing neural networks for at least one of the following applications: motion planning, object detection, sensor fusion, motion prediction, and/or multi-object tracking
Strong track record of tackling less well-defined problems, and executing efficiently to deliver the successful outcome
Advanced knowledge of software engineering principles including software design, source control management, build processes, code reviews, and testing methods
Experience with PyTorch or other python-based deep learning frameworks
Experience working with large data sets and deriving insights from data
Experience mentoring and collaborating with others

Education
Masters or PhD in Machine Learning, Computer Science, Applied Mathematics, Statistics, Physics or a related field; or equivalent industry experience

Bonus Points

Publications in relevant conferences (CVPR, ICML, NeurIPS, ICCV, ICL, etc.)
PhD in machine learning, computer vision, or robotics vision
Experience working on autonomous vehicles or related fields
Experience in deploying models into real-world environments
Strong programming skills in C++ and/or CUDA programming
This opportunity can support remote work within the United States, with occasional travel.

Working Conditions

While performing the duties of this job, the employee is frequently required to convey and detect communication

The employee occasionally required to remain stationary at times for up to 50% of working time, move in designated working areas; & operate and use office equipment

The employee may occasionally move up to 50 pounds

The salary range for this role is an estimate based on a wide range of compensation factors including but not limited to specific skills, experience and expertise, role location, certifications, licenses, and business needs. The estimated compensation range listed in this job posting reflects base salary only. This role may include additional forms of compensation such as a bonus or company equity. The recruiter assigned to this role can share more information about the specific compensation and benefit details associated with this role during the hiring process.

Candidates for certain positions are eligible to participate in Motional’s benefits program. Motional’s benefits include but are not limited to medical, dental, vision, 401k with a company match, health saving accounts, life insurance, pet insurance, and more.

Salary Range$146,000—$225,000 USD

Motional is a driverless technology company making autonomous vehicles a safe, reliable, and accessible reality. We’re driven by something more.

Our journey is always people first.

We aren't just developing driverless cars; we're creating safer roadways, more equitable transportation options, and making our communities better places to live, work, and connect. Our team is made up of engineers, researchers, innovators, dreamers and doers, who are creating a technology with the potential to transform the way we move.

Higher purpose, greater impact.

We’re creating first-of-its-kind technology that will transform transportation. To do so successfully, we must design for everyone in our cities and on our roads. We believe in building a great place to work through a progressive, global culture that is diverse, inclusive, and ensures people feel valued at every level of the organization. Diversity helps us to see the world differently; it’s not only good for our business, it’s the right thing to do.

Scale up, not starting up.

Our team is behind some of the industry's largest leaps forward, including the first fully-autonomous cross-country drive in the U.S, the launch of the world's first robotaxi pilot, and operation of the world's longest-standing public robotaxi fleet. We’re driven to scale; we’re moving towards commercialization of our technology, and we need team members who are ready to embrace change and challenges.

Formed as a joint venture between Hyundai Motor Group and Aptiv, Motional is fundamentally changing how people move through their lives. Headquartered in Boston, Motional has operations in the U.S and Asia. For more information, visit www.Motional.com and follow us on Twitter, LinkedIn, Instagram and YouTube.

Motional AD Inc. is an EOE. We celebrate diversity and are committed to creating an inclusive environment for all employees. To comply with Federal Law, we participate in E-Verify. All newly-hired employees are queried through this electronic system established by the DHS and the SSA to verify their identity and employment eligibility.

","hiringOrganization":{"@type":"Organization","name":"Motional","sameAs":"https://motional.com/"},"jobLocation":{"@type":"Place","address":{"@type":"PostalAddress","addressLocality":"Boston, Massachusetts, United States; Pittsburgh, Pennsylvania, United States; Remote U.S.","addressCountry":"United States","addressRegion":"North America"}}}},{"@type":"ListItem","position":20,"item":{"@type":"JobPosting","title":"Senior Machine Learning Engineer","datePosted":"2025-09-23","description":"

Federato is on a mission to defend the right to efficient, equitable insurance for all. We enable insurers to provide affordable coverage to people and organizations facing the issues of today - the climate crisis, cyber-attacks, social inflation, etc. Our vision is understood and well funded by those behind Salesforce, Veeva, Zoom, Box, etc.

Federato’s AI/ML-driven platform leverages deep reinforcement learning to help insurance companies optimize the portfolio of risks they insure, allowing them to continue to provide fair and equitable pricing in difficult-to-price areas. Our category-defining ‘RiskOps’ solution drives better underwriting decisions by operationalizing underutilized data investments and surfacing real-time risk and portfolio insights. We focus on putting insurance underwriters back in the driver’s seat, helping them meet their goals while providing an important service to society.

What You'Ll Be Doing:

Design and implement scalable machine learning pipelines, serving prompt engineering workflows to enhance scalability and efficiency in submission intake processes across multiple insurance use cases.
Collaborate cross-functionally, serving as a technical lead for junior team members, providing mentorship and guidance to elevate team performance and technical knowledge.
Ensure production-grade deployment standards, emphasizing scalability, reliability, and compliance with insurance data handling policies, balancing rapid iteration with stability.
Build reusable, modular infrastructure components and CI/CD pipelines for ML and LLM workloads, enabling rapid experimentation and seamless transition from research to production.
Champion best practices in observability, testing, and monitoring of ML systems, establishing standards for model/data drift detection, logging, and automated rollback strategies.

Who We Hope You Are:

Proven experience as a Machine Learning Engineer or similar role (at least 5 years), with a strong focus on pipelining LLM models over the last 2 years.
Proven experience in designing scalable and robust machine learning pipelines, both for classical machine learning and large language models (LLMs) along with familiarity with open-source models is a plus.
Experience in building scalable ML pipelines using tools such as Kubeflow. Knowledge of automating and monitoring ML workflows to ensure consistent model performance in production.
Hands-on experience with cloud platforms, including deploying models, managing cloud resources, and using relevant APIs for data intake, storage, and processing
Great communication skills with the ability to convey complex findings to non-technical audiences.

\n\n

$180,000 - $220,000 a year
Final offer amounts are determined by multiple factors including candidate location, experience and expertise and may vary from the amounts listed above. Total compensation package does include stock options, benefits and additional perks.

Here at Federato, your capabilities are important, but culture fit is quintessential. We move fast, are eager to listen to our users, take a first principles approach to solving problems, and value learning and the ability to change our minds. Most importantly, we're here to have fun. Our ability to make a difference starts with our people. We would love to work with you!

We are an equal-opportunity employer and value diversity at our company. We do not discriminate on the basis of race, religion, color, national origin, sex, gender expression, sexual orientation, age, marital status, veteran status or disability status. We will provide reasonable accommodation to individuals with disabilities to participate in the job application or interview process, to perform essential job functions, and to receive other benefits and privileges of employment. Please contact us to request accommodation at talent@federato.ai

","hiringOrganization":{"@type":"Organization","name":"Federato","sameAs":"https://www.federato.ai/"},"jobLocation":{"@type":"Place","address":{"@type":"PostalAddress","addressLocality":"Remote"}}}},{"@type":"ListItem","position":21,"item":{"@type":"JobPosting","title":"Machine Learning Engineer Intern (Summer 2026)","datePosted":"2025-09-23","description":"

At Klaviyo, we value the unique backgrounds, experiences and perspectives each Klaviyo (we call ourselves Klaviyos) brings to our workplace each and every day. We believe everyone deserves a fair shot at success and appreciate the experiences each person brings beyond the traditional job requirements. If you’re a close but not exact match with the description, we hope you’ll still consider applying.

At Klaviyo, we believe the future of software lies not in productivity tools for human users but in software that can run and optimize itself based on outcome or reward metrics. We’ve built the infrastructure and application that serve as the interface between businesses and consumers. We now have over 167,000 customers, billions of consumer profiles, and hundreds of billions of customer messages and follow-on conversion data. We have a big opportunity to build state-of-the-art AI and machine learning technologies at Klaviyo to power our products and develop AI agents that can automatically create and execute marketing or customer experiences, strategies, and campaigns for any business.

As a Machine Learning Engineer Intern at Klaviyo, you will work with a team of Machine Learning and Full-stack engineers to build models that extract insights from the massive streams of data that Klaviyo ingests continuously. You will apply cutting-edge techniques from deep learning, language modeling, recommender systems, and more to integrate artificial intelligence into our product and bring customers value. You will be a contributing member of the team, learning from experienced engineers and helping to set the standard for excellence. You should have foundational knowledge in machine learning or data science, especially in the domain of deep learning, recommender systems, NLP, generative AI, or related areas.

\n\n

Things you’ll do & make a difference

Build high-impact ML systems, tackling challenges such as model development, deployment, and scale, with direct ownership of high impact systems.
Contribute to the modeling & system design and implementation decisions.
Contribute to the development and execution of technical strategies that align with Klaviyo's business goals, ensuring products are not only exceptional but also aligned with the broader vision for a reliable and user-friendly AI/ML platform.
Engage with internal stakeholders to understand their needs and resolve blockers.
Learn and improve upon engineering-wide processes like recruiting, performance development, communication, and agile development.
Stay abreast of emerging AI trends and technologies, identifying and leveraging opportunities for their application within Klaviyo’s ecosystem.
Work with the team on project planning and defining achievements, identifying dependencies, and meeting business goals.

What We Are Looking For:

Pursuing an advanced degree Phd preferred in Computer Science, Artificial Intelligence, Machine Learning, or a related field, Graduating in December 2026 or May/June 2027

Previous internship experience in AI, machine learning, or related fields, with a strong interest in building and deploying machine learning projects.
Good communication skills, capable of collaborating with team members and learning from stakeholders.
Foundational understanding through prior internships and projects of AI technologies and their application in business contexts, including deep learning, recommendation systems, NLP, generative AI, or related areas.
Ability to code in Python and use standard ML technologies such as PyTorch.

Nice To Have:

Experience with large-scale data processing tools including Spark

\n\n

We use Covey as part of our hiring and / or promotional process. For jobs or candidates in NYC, certain features may qualify it as an AEDT. As part of the evaluation process we provide Covey with job requirements and candidate submitted applications. We began using Covey Scout for Inbound on April 3, 2025.

Please see the independent bias audit report covering our use of Covey here

Massachusetts Applicants:
It is unlawful in Massachusetts to require or administer a lie detector test as a condition of employment or continued employment. An employer who violates this law shall be subject to criminal penalties and civil liability.

\n\n

Our salary range reflects the cost of labor across various U.S. geographic markets. The range displayed below reflects the minimum and maximum target salaries for the position across all our US locations. The base salary offered for this position is determined by several factors, including the applicant’s job-related skills, relevant experience, education or training, and work location.

In addition to base salary, our total compensation package may include participation in the company’s annual cash bonus plan, variable compensation (OTE) for sales and customer success roles, equity, sign-on payments, and a comprehensive range of health, welfare, and wellbeing benefits based on eligibility. Please visit Klaviyo Rewards to find out more about our Total Rewards package.

Your recruiter can provide more details about the specific salary/OTE range for your preferred location during the hiring process.

Base Pay Range For US Locations:$58—$58 USD

Get to Know Klaviyo

We’re Klaviyo (pronounced clay-vee-oh). We empower creators to own their destiny by making first-party data accessible and actionable like never before. We see limitless potential for the technology we’re developing to nurture personalized experiences in ecommerce and beyond. To reach our goals, we need our own crew of remarkable creators—ambitious and collaborative teammates who stay focused on our north star: delighting our customers. If you’re ready to do the best work of your career, where you’ll be welcomed as your whole self from day one and supported with generous benefits, we hope you’ll join us.

Klaviyo is committed to a policy of equal opportunity and non-discrimination. We do not discriminate on the basis of race, ethnicity, citizenship, national origin, color, religion or religious creed, age, sex (including pregnancy), gender identity, sexual orientation, physical or mental disability, veteran or active military status, marital status, criminal record, genetics, retaliation, sexual harassment or any other characteristic protected by applicable law.

\n\n\n\n\n\n\n\n\n\n\n\nIMPORTANT NOTICE: Our company takes the security and privacy of job applicants very seriously. We will never ask for payment, bank details, or personal financial information as part of the application process. All our legitimate job postings can be found on our official career site. Please be cautious of job offers that come from non-company email addresses (@klaviyo.com), instant messaging platforms, or unsolicited calls. You can find our Job Applicant Privacy Notice here.\n \nBy clicking \"Submit Application\" you consent to Klaviyo processing your Personal Data in accordance with our Job Applicant Privacy Notice. If you do not wish for Klaviyo to process your Personal Data, please do not submit an application. You can find our Job Applicant Privacy Notice here.","hiringOrganization":{"@type":"Organization","name":"Klaviyo","sameAs":"https://www.klaviyo.com/"},"jobLocation":{"@type":"Place","address":{"@type":"PostalAddress","addressLocality":"Boston, MA","addressCountry":"United States","addressRegion":"North America"}}}},{"@type":"ListItem","position":22,"item":{"@type":"JobPosting","title":"Machine Learning Engineer","datePosted":"2025-09-23","description":"

Company Description

Job Description

What you get to do in this role:

You will play a major part in building AI and Machine Learning (ML) solutions that transform the user experience and workflow efficiency of enterprise services. Traditional analytical tools tend to require a technically knowledgeable user to produce even simple results. We are taking a completely fresh approach with the expectation that any user, regardless of technical knowledge, can use the AI/ML solutions we develop to operate the services in the enterprise setting in a thoughtful and scalable manner. We are just getting started with our early-adopter customers and we need your help in building and making available an amazing range of solutions to our 5k+ enterprise customers around the world.

Build the best cloud-based AI/ML solutions to power intelligent enterprise services
Collaborate daily with a team of like-minded developers, product managers and quality engineers to produce quality software
Work with product owners to understand detailed requirements and own your code from design, implementation, testing and delivery of high-quality solutions to our users

Qualifications

To be successful in this role you have:

A Bachelor's degree and 2+ years of related experience; or an advanced degree without experience; or equivalent work experience
Proficient in prompt engineering and developing LLM based features
Experience with methods of training and fine tuning large language models, such as distilation, supervised fine-tunning and policy optimization
Experience in using Al productivity tools such as Cursor, Windsurf, etc. is a plus or nice to have
Experience in leveraging or critically thinking about how to integrate AI into work processes, decision-making, or problem-solving. This may include using AI-powered tools, automating workflows, analyzing AI-driven insights, or exploring AI’s potential impact on the function or industry
Expertise in Java or Python, OOP, Design Patterns, time and space-efficient algorithms
Experience building new products that use challenging algorithms
Expertise in coding efficient, object-oriented, modularized and quality software
Knowledge of core AI/ML techniques and algorithms
Knowledge of unit testing, profiling, and code tuning

For positions in this location, we offer a base pay of $137,300 - $212,900, plus equity (when applicable), variable/incentive compensation and benefits. Sales positions generally offer a competitive On Target Earnings (OTE) incentive compensation structure. Please note that the base pay shown is a guideline, and individual total compensation will vary based on factors such as qualifications, skill level, competencies, and work location. We also offer health plans, including flexible spending accounts, a 401(k) Plan with company match, ESPP, matching donations, a flexible time away plan and family leave programs. Compensation is based on the geographic location in which the role is located and is subject to change based on work location.

Additional Information

Work Personas

Equal Opportunity Employer

Accommodations

Export Control Regulations

","hiringOrganization":{"@type":"Organization","name":"ServiceNow","sameAs":"https://www.servicenow.com"},"jobLocation":{"@type":"Place","address":{"@type":"PostalAddress","addressLocality":"Santa Clara, California , United States","addressCountry":"United States","addressRegion":"North America"}}}},{"@type":"ListItem","position":23,"item":{"@type":"JobPosting","title":"Machine Learning Engineer (Python)- IFS TheLoops","datePosted":"2025-09-23","description":"

Company Description

IFS is a billion-dollar revenue company with 7000+ employees on all continents. Our leading AI technology is the backbone of our award-winning enterprise software solutions, enabling our customers to be their best when it really matters–at the Moment of Service™. Our commitment to internal AI adoption has allowed us to stay at the forefront of technological advancements, ensuring our colleagues can unlock their creativity and productivity, and our solutions are always cutting-edge.

At IFS, we’re flexible, we’re innovative, and we’re focused not only on how we can engage with our customers but on how we can make a real change and have a worldwide impact. We help solve some of society’s greatest challenges, fostering a better future through our agility, collaboration, and trust.

We celebrate diversity and understand our responsibility to reflect the diverse world we work in. We are committed to promoting an inclusive workforce that fully represents the many different cultures, backgrounds, and viewpoints of our customers, our partners, and our communities. As a truly international company serving people from around the globe, we realize that our success is tantamount to the respect we have for those different points of view.

By joining our team, you will have the opportunity to be part of a global, diverse environment; you will be joining a winning team with a commitment to sustainability; and a company where we get things done so that you can make a positive impact on the world.

We’re looking for innovative and original thinkers to work in an environment where you can #MakeYourMoment so that we can help others make theirs. With the power of our AI-driven solutions, we empower our team to change the status quo and make a real difference.

If you want to change the status quo, we’ll help you make your moment. Join Team Purple. Join IFS.

Job Description

We are looking for a motivated Machine Learning Engineer (Python) to join our fast-moving team. This is a hands-on role ideal for someone with a solid foundation in machine learning, strong Python skills, and a desire to grow in a dynamic and often ambiguous environment. You’ll work closely with product managers, data scientists, and engineers to rapidly prototype, test, and deploy ML-driven features and pipelines.

What You’Ll Do

Collaborate in an agile team to develop and deploy ML models and data pipelines.
Translate loosely defined business or customer requirements into practical ML solutions.
Be creative and proactive in shaping solutions that solve real-world problems.
Build, test, and optimize scalable Python-based systems for training and inference.
Work with structured and unstructured data (e.g., tabular, text, image).
Participate in sprint planning, daily stand-ups, and reviews.
Own and maintain parts of the codebase and contribute to improving engineering best practices.

Qualifications

What We’re Looking For

2–4 years of experience in software engineering or ML engineering roles.
Strong Python programming skills with experience in ML frameworks like scikit-learn, TensorFlow, or PyTorch.
Proficiency with data handling libraries (e.g., pandas, NumPy) and tools like Jupyter.
Ability to take customer or business requirements and creatively turn them into technical solutions.
Exposure to common ML workflows: data cleaning, feature engineering, model evaluation.
Comfortable working in a fast-paced, agile environment with changing priorities and some ambiguity.
Good communication and collaboration skills; you’re proactive and not afraid to ask questions.
Familiarity with version control (e.g., Git) and containerization (e.g., Docker).
Experience with cloud platforms (AWS, GCP, or Azure) and basic understanding of MLOps practices.
Exposure to CI/CD workflows and tools like MLflow or model serving frameworks.
Ability to build lightweight APIs (e.g., FastAPI, Flask) to expose models is a plus.

Additional Information

We embrace flexibility and hybrid work opportunities to support diverse needs and lifestyles, while also valuing inclusive workplace experiences. By fostering a sense of community, we drive innovation, strengthen connections, and nurture belonging. Our commitment ensures you can work in a way that suits you best, while also engaging with colleagues to share ideas and build meaningful relationships.

","hiringOrganization":{"@type":"Organization","name":"IFS","sameAs":"https://www.ifs.com/"},"jobLocation":{"@type":"Place","address":{"@type":"PostalAddress","addressLocality":"Colombo, WP, Sri Lanka","addressCountry":"Sri Lanka","addressRegion":"Asia/Pacific"}}}},{"@type":"ListItem","position":24,"item":{"@type":"JobPosting","title":"Machine Learning Engineer, NLP and multimodal","datePosted":"2025-09-23","description":"

About Newsbreak

Founded in 2015, NewsBreak is the Content Intelligence platform shaping the future content economy. With over 40 million monthly active users, our flagship platform delivers highly personalized local news and information powered by advanced AI, recommendation systems, and adtech.

Recognized by Fast Company as #32 on the Top Workplaces for Innovators, we're proud to be Great Place to Work® certified and home to a dynamic team of technologists, product innovators, and business leaders who are passionate about solving meaningful challenges at scale.

Together, we reached unicorn status in 2021, and we remain committed to continuing this high-growth trajectory with the right team to fulfill our mission: building the infrastructure layer for content intelligence.

If you’re inspired to dream big, innovate fast, and make a difference, we’d love to hear from you! For more information, visit www.newsbreak.com/about

Location: Onsite 5 days in Mountain View, CA office \n

About The Role

We are seeking a talented Multimodal Machine Learning Engineer to join our fast-growing machine learning team. Our company develops a range of products that leverage multimodal signals—including audio, video, text, and images—to deliver cutting-edge AI-powered experiences. As part of our team, you will play a crucial role in advancing machine learning and generative AI technologies to enhance user engagement and drive innovation across our products. With strong organizational support, a clear vision, and a vast scope of impact, this role provides the opportunity to tackle real-world challenges, pioneer transformative solutions, and shape the future of multimodal AI. We foster a dynamic and collaborative research environment that encourages innovation with state-of-the-art technologies and novel ideas. If you're passionate about pushing the boundaries of AI and multimodal learning, we invite you to be a part of our journey.

Responsibilities

Design and develop state-of-the-art multimodal AI solutions for understanding and generating content across video, image, audio/speech.
Create innovative technologies to improve automated content generation for multiple modalities.
Contribute to the development of new AI-driven products and tools that push the boundaries of multimodal machine learning.

Requirements

MS degree with 2+ years of experience or a PhD in Computer Science, Machine Learning, or a related field.
Strong background in machine learning technologies, such as Large Language Models, Diffusion Model, Computer Vision, Video Processing, Audio/Speech Processing.
Proficiency in programming languages such as Python.
Familiarity with databases and data storage solutions like MongoDB, Redis, and SQL.
A strong passion for emerging technologies, with demonstrated analytical and problem-solving abilities.
Excellent communication, teamwork, and project management skills.

Preferred

A proven research record, including publications in top machine learning/AI transactions/conference.

Why Join Us?

Work on impactful, cutting-edge technologies that reach tens of millions of users.
Collaborate with a team of passionate AI researchers and engineers.
Opportunity to pioneer innovative AI products in a fast-growing domain. If you're passionate about shaping the future of multimodal machine learning and generative AI, we'd love to hear from you!

Benefits

We offer a competitive benefits package:

Health, dental, and vision care for you and your family (100% coverage for employee)
Top-tier 401(K) plan with company matching
Paid time off and paid holidays
FSA, HSA and commuter benefits programs
Team activity budget

\nThe US base salary range for this full-time position is listed below. Pay may vary based on a number of factors including job-related skills, level, experience, geographic location and relevant education or training. At NewsBreak, we design our overall rewards package to attract top talents. Depending on the position, the role may also be eligible for discretionary bonus and options. Your recruiter can share more details during the hiring process.Annual Base Pay Range$130,000—$260,000 USD

CPRA Privacy Notice for California Candidates

\n","hiringOrganization":{"@type":"Organization","name":"NewsBreak","sameAs":"https://www.newsbreak.com/"},"jobLocation":{"@type":"Place","address":{"@type":"PostalAddress","addressLocality":"Mountain View, California, United States","addressCountry":"United States","addressRegion":"North America"}}}},{"@type":"ListItem","position":25,"item":{"@type":"JobPosting","title":"Machine Learning Engineer - Intern","datePosted":"2025-09-23","description":"We Make a Future Classic Product!
채널톡은 기업의 지속가능한 성장을 돕는 ‘올인원 AI 메신저’입니다. 고객과 언제 어디서나 대화할 수 있는 환경을 만들어 비즈니스의 방향성을 고객으로부터 찾을 수 있도록 돕고 있어요.
현재 '고객이 답이다'라는 철학으로 고객사의 고객 소통 경험을 변화시키고 있습니다. CRM 데이터 기반의 상담 경험 설계와 AI를 통한 반복 문의를 빠르게 처리해 CS 효율화부터 고객 경험 개선까지 채널톡 하나로 해결해요.
수많은 온라인 비즈니스의 본질적인 문제를 풀어낸 결과 한국 너머의 시장에서도 빠르게 성장하고 있습니다. 일본 시장에서 점유율 20% 이상으로 업계 1위와 매출 성장세도 B2B 업체 중 아시아에서 가장 빠른 수준이에요. 아시아에서 인정받은 제품력을 발판 삼아 글로벌 SaaS 기업으로 거듭나고자 미국 시장에 적극 진출하고 있습니다.
채널톡 출시 이후 이와 같은 성과를 거둘 수 있었던 핵심은 ‘제품’입니다. 좋은 제품이 최고의 세일즈, 마케팅이라고 믿습니다. 채널팀 전체 임직원 중 절반 이상이 개발자로 이들 모두가 단 하나의 제품을 만드는데 집중합니다. 구글 검색, 아이폰처럼 한 세대를 상징할 “미래의 클래식” 프로덕트를 목표로 최고의 인재들과 함께합니다.
하고 싶은 일이 참 많습니다! 많이 기대되는 앞으로의 여정 가운데 함께할 채널톡의 Machine Learning Engineer - Intern을 찾습니다!
[채널팀이 더욱 궁금하다면?🧐]🏡 홈페이지💡블로그🖥 유튜브💌 인스타그램\n

어떤 기회가 있나요?🚀

상담 문제를 넘어, 비즈니스 전반에서 AI 기술로 고객의 문제를 해결하는 과정을 end-to-end로 경험할 수 있습니다.
채팅 및 음성 기반의 상담봇 시스템에 필요한 기반 기술 연구를 직접 주도적으로 하실 수 있습니다.
데이터셋 및 학습된 모델 공개 등으로 오픈 소스 커뮤니티에 기여할 수 있습니다.
최신 LLM 기반 음성 모델 연구에 참여할 수 있습니다.

어떤 업무를 담당하나요?🤔

상담 에이전트 서비스 (ALF) 개선
텍스트, 오디오 등 도메인의 특성에 맞게 최적화된 에이전트 구현
단순 질의응답이 아닌 다양한 태스크를 수행할 수 있는 에이전트 워크플로우 개선
Context engineering을 통한 에이전트 성능 개선
상담 에이전트 평가용 내부 벤치마크 구축 및 개선

데이터 전처리 파이프라인 구축 및 학습
다양한 소스로부터 주어진 문제에 적합한 데이터 수집 및 퀄리티 관리
모델 및 파이프라인 최적화로 효율적인 전처리 파이프라인 구축 (Ray 기반 분산처리, inference acceleration)
다양한 데이터 레시피로 LLM 및 Flow Matching 기반 모델 학습 실험 수행

어떤 경력과 역량이 필요한가요?📖

컴퓨터 과학, 전자공학, 수학, 통계학 등 해당 포지션과 관련된 전공의 학사 이상의 학위를 가지고 계신 분
LLM 모델에 대한 구체적인 이해 및 실제 학습 경험
목표에 맞는 데이터 구축 및 학습 레시피 구축 경험
모호한 상황에서의 문제 정의, 액션 아이템 도출, 실행 및 평가 등 문제 해결 파이프라인을 반복적으로 빠르게 수행하실 수 있는 분
Python 및 LLM 개발 관련 Library나 Platform(PyTorch, Hugging Face) 활용 능력을 갖추신 분

이런 점이 있으면 더 좋아요😊

관련 전공 석사 이상의 학위를 가지고 계신 분
대량의 데이터셋을 수집하고 정제한 경험이 있으신 분
AI 주제의 논문을 작성해보시거나 오픈소스 및 경진대회 활동 경력이 있으신 분
LLM 기반 AI 에이전트를 Production 레벨에서 구현/배포/운영해본 경험이 있으신 분

어떤 방식으로 채용하나요?🏃

일반적으로 서류 제출 - 1차 인터뷰 - 2차 인터뷰 순서로 진행됩니다.
제출하신 서류를 통해 팀에 필요한 기본적인 문제해결 역량을 가지신 분인지 확인합니다. 지금까지 진행하셨던 프로젝트들과 도전 과제들을 어떻게 해결하셨는지 적어주시면 많은 도움이 됩니다.
1차 인터뷰는 1시간 소요되며, 수행하셨던 프로젝트에 대한 내용을 발표하고 관련 질의응답을 진행하게 됩니다. 지원자의 창의적인 문제 해결 능력을 확인하는 데에 중점을 둡니다. 결과 뿐만 아니라 문제를 해결해가는 과정 자체도 중요하게 평가합니다.
2차 인터뷰는 1시간 소요됩니다. 채널과 핏이 잘 맞는 분인지 알기 위해 편안하게 서로 질문을 할 수 있는 시간을 갖게 됩니다.
채용 프로세스는 과제나 면접 결과에 따라 면접 절차를 유동적으로 조정될 수 있습니다.

[아래의 개인정보 처리방침에 동의하고 입사지원하시는 경우 지원자의 개인정보는 다음과 같이 국외이전 됨을 확인하고 동의 합니다.]- 이전받는 자 및 이전 되는 국가 : Lever / 미국- 이전되는 개인정보 항목 : 이름, 이메일, 연락처 및 관련서류- 이전목적 및 보유기간 : 채용절차 진행 / 2년**개인정보 국외이전에 동의하지 않을 수 있으나 최종 입사지원서 제출이 불가하며, 지원하기를 누르시면 동의함으로 간주합니다.","hiringOrganization":{"@type":"Organization","name":"Channel Talk","sameAs":"https://channel.io/"},"jobLocation":{"@type":"Place","address":{"@type":"PostalAddress","addressLocality":"서울 강남구 논현로 508, GS강남타워","addressCountry":"South Korea","addressRegion":"Asia/Pacific"}}}},{"@type":"ListItem","position":26,"item":{"@type":"JobPosting","title":"Lead Machine Learning Engineer","datePosted":"2025-09-23","description":"

About The Role:

Grade Level (For Internal Use):

About The Role:

We are seeking a Lead Machine Learning and MLOps Engineer focused on Generative AI to join our ML team within the Data Science Center of Excellence at S&P Global. In this role, you will lead engineering activities to build production-grade generative AI solutions and play a pivotal role in implementing machine learning engineering operations to ensure seamless deployment, monitoring, and management of our machine learning models and data pipelines.

The Team:

You will work closely with a world-class AI and ML team comprised of experts in AI and ML modeling, MLOps engineers, data science, and data engineering. Your contributions will be critical in engineering and developing solutions for ML operations, supporting S&P’s AI-driven transformation to drive value both internally and for our customers. This role presents a unique opportunity for ML/MLOps engineers to advance in their career journey.

Responsibilities And Impact:

Lead ML Engineering to architect, build, and deploy production-grade generative AI services and solutions.
Work on large-scale distributed systems, including infrastructure, data ingestion platforms, relational and non-relational databases, microservices, orchestration services, and more.
Oversee MLOps platform development and automated pipelines focused on deploying, monitoring, and maintaining models in production environments, ensuring model governance and optimizing cost and performance.
Collaborate with cross-functional teams to integrate machine learning models into production systems.
Create and manage documentation and knowledge base, including development best practices and MLOps processes and procedures.
Work closely with technology teams in the development and implementation of an enterprise AI platform..

What We’Re Looking For:

Basic Required Qualifications:

Bachelor's degree in Computer Science, Engineering, or a related field.
5 years of progressive experience in machine learning, data analytics, or similar roles.
5 years of relevant experience in:
Writing production-level, scalable code.
MLOps, machine learning engineering, big data, or a related role.
Working with relational and non-relational databases, data processing frameworks, and data orchestration.
Containerization, cloud platforms, CI/CD, and workflow orchestration.
Distributed systems programming and AI/ML solutions architecture.

Additional Preferred Qualifications:

2-3 years of experience operationalizing data-driven pipelines for large-scale batch and stream processing analytics solutions.
Experience contributing to research projects or participating in data science competitions.
6-12 months of experience working with generative AI use cases and relevant engineering practices.

About S&P Global Ratings
At S&P Global Ratings, our analyst-driven credit ratings, research, and sustainable finance opinions provide critical insights that are essential to translating complexity into clarity so market participants can uncover opportunities and make decisions with conviction. By bringing transparency to the market through high-quality independent opinions on creditworthiness, we enable growth across a wide variety of organizations, including businesses, governments, and institutions.

S&P Global Ratings is a division of S&P Global (NYSE: SPGI). S&P Global is the world’s foremost provider of credit ratings, benchmarks, analytics and workflow solutions in the global capital, commodity and automotive markets. With every one of our offerings, we help many of the world’s leading organizations navigate the economic landscape so they can plan for tomorrow, today.

For more information, visit www.spglobal.com/ratings

What’s In It For You?

Our Purpose:

Progress is not a self-starter. It requires a catalyst to be set in motion. Information, imagination, people, technology–the right combination can unlock possibility and change the world.

Our world is in transition and getting more complex by the day. We push past expected observations and seek out new levels of understanding so that we can help companies, governments and individuals make an impact on tomorrow. At S&P Global we transform data into Essential Intelligence®, pinpointing risks and opening possibilities. We Accelerate Progress.

Our People:

We're more than 35,000 strong worldwide—so we're able to understand nuances while having a broad perspective. Our team is driven by curiosity and a shared belief that Essential Intelligence can help build a more prosperous future for us all.

From finding new ways to measure sustainability to analyzing energy transition across the supply chain to building workflow solutions that make it easy to tap into insight and apply it. We are changing the way people see things and empowering them to make an impact on the world we live in. We’re committed to a more equitable future and to helping our customers find new, sustainable ways of doing business. We’re constantly seeking new solutions that have progress in mind. Join us and help create the critical insights that truly make a difference.

Our Values:

Integrity, Discovery, Partnership

At S&P Global, we focus on Powering Global Markets. Throughout our history, the world's leading organizations have relied on us for the Essential Intelligence they need to make confident decisions about the road ahead. We start with a foundation of integrity in all we do, bring a spirit of discovery to our work, and collaborate in close partnership with each other and our customers to achieve shared goals.

Benefits:

We take care of you, so you can take care of business. We care about our people. That’s why we provide everything you—and your career—need to thrive at S&P Global.
Our benefits include:
Health & Wellness: Health care coverage designed for the mind and body.
Flexible Downtime: Generous time off helps keep you energized for your time on.
Continuous Learning: Access a wealth of resources to grow your career and learn valuable new skills.
Invest in Your Future: Secure your financial future through competitive pay, retirement planning, a continuing education program with a company-matched student loan contribution, and financial wellness programs.
Family Friendly Perks: It’s not just about you. S&P Global has perks for your partners and little ones, too, with some best-in class benefits for families.
Beyond the Basics: From retail discounts to referral incentive awards—small perks can make a big difference.

For more information on benefits by country visit: https://spgbenefits.com/benefit-summaries

Global Hiring and Opportunity at S&P Global:

At S&P Global, we are committed to fostering a connected and engaged workplace where all individuals have access to opportunities based on their skills, experience, and contributions. Our hiring practices emphasize fairness, transparency, and merit, ensuring that we attract and retain top talent. By valuing different perspectives and promoting a culture of respect and collaboration, we drive innovation and power global markets.

S&P Global has a Securities Disclosure and Trading Policy (“the Policy”) that seeks to mitigate conflicts of interest by monitoring and placing restrictions on personal securities holding and trading. The Policy is designed to promote compliance with global regulations. In some Divisions, pursuant to the Policy’s requirements, candidates at S&P Global may be asked to disclose securities holdings. Some roles may include a trading prohibition and remediation of positions when there is an effective or potential conflict of interest. Employment at S&P Global is contingent upon compliance with the Policy.

Recruitment Fraud Alert:

If you receive an email from a spglobalind.com domain or any other regionally based domains, it is a scam and should be reported to reportfraud@spglobal.com. S&P Global never requires any candidate to pay money for job applications, interviews, offer letters, “pre-employment training” or for equipment/delivery of equipment. Stay informed and protect yourself from recruitment fraud by reviewing our guidelines, fraudulent domains, and how to report suspicious activity here.

-----------------------------------------------------------

Equal Opportunity Employer

S&P Global is an equal opportunity employer and all qualified candidates will receive consideration for employment without regard to race/ethnicity, color, religion, sex, sexual orientation, gender identity, national origin, age, disability, marital status, military veteran status, unemployment status, or any other status protected by law. Only electronic job submissions will be considered for employment.

If you need an accommodation during the application process due to a disability, please send an email to: EEO.Compliance@spglobal.com and your request will be forwarded to the appropriate person. 

US Candidates Only: The EEO is the Law Poster http://www.dol.gov/ofccp/regs/compliance/posters/pdf/eeopost.pdf describes discrimination protections under federal law. Pay Transparency Nondiscrimination Provision - https://www.dol.gov/sites/dolgov/files/ofccp/pdf/pay-transp_%20English_formattedESQA508c.pdf

-----------------------------------------------------------

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We are looking for individuals who are passionate about pushing the boundaries of computer vision while also delivering efficient, production-ready models. Candidates with a strong record of open-source contributions or a demonstrable portfolio of impactful ML projects will stand out.

Key Responsibilities

Design, implement, and optimize image/video ML models for large-scale generative AI applications.
Apply advanced techniques such as quantization, pruning, fine-tuning, and model distillation to improve efficiency and performance.
Work with deployment frameworks (ONNX, TensorRT, CUDA) to enable scalable inference.
Collaborate with researchers to bridge state-of-the-art techniques with production-grade engineering.
Conduct experiments, benchmark models, and document findings.
Share insights and collaborate with the broader ML research/engineering team.
Bachelor’s, Master’s, or PhD in Computer Science, AI, Machine Learning, or related fields.
Hands-on experience with deep learning frameworks: PyTorch (preferred), TensorFlow, or JAX.
Strong background in optimization techniques (quantization, pruning, distillation, mixed precision).
Experience with deployment toolkits: ONNX, TensorRT, CUDA, or similar.

Required Qualifications

Demonstrated work in image/video model training, fine-tuning, or adaptation.
Proficiency in Python and familiarity with large-scale GPU-based training.
Experience with GGUF, ComfyUI, or other model deployment ecosystems.
Contributions to open-source computer vision or ML frameworks.
Research or industry experience with foundational/generative models (diffusion, transformers, multimodal).
Familiarity with scaling ML models in distributed systems.
Please share your GitHub profile showcasing open-source work in ML/Computer Vision.

Preferred Qualifications

Portfolio / Contribution Requirement

If unavailable, provide a portfolio of projects, research papers, or documented achievements in model development, training, or optimization.

","hiringOrganization":{"@type":"Organization","name":"Vyro","sameAs":"https://vyro.ai/"},"jobLocation":{"@type":"Place","address":{"@type":"PostalAddress","addressLocality":"China, China","addressCountry":"China","addressRegion":"Asia/Pacific"}}}},{"@type":"ListItem","position":28,"item":{"@type":"JobPosting","title":"Machine Learning Engineer","datePosted":"2025-09-23","description":"

Job Summary

SGX is looking for a Machine Learning Engineer who is passionate about building scalable data/machine learning platforms and pioneering solutions. As a Machine Learning Engineer, you will play a crucial role in transforming how we run and deploy AI/ML models. Your work will directly impact our ability to build and deliver AI/ML use cases that will augment our users in their work or enable business opportunities. By enhancing our machine learning platform, you will enable us to make data-driven decisions and drive innovation across the organization. This is a 2-year contract role with an option for extension.

Job Responsibilities

Design and build scalable data platforms (including machine learning platforms) to support AI/GenAI use cases, streamline data storage, democratization, model deployment, and support feature engineering, model training, deployment, model monitoring and inference.
Develop and integrate data pipelines for continuous development, integration, testing, and scalable machine learning services.
Migrate existing data science projects to the new cloud machine learning platform.
Collaborate with data scientists and data engineers to design, implement, and integrate data pipelines.
Improve/automate existing model training, feature engineering, and evaluation pipelines, enabling the feedback loop of taking in labelled data from users/source systems for model re-training/tuning.
Design and develop CI/CD pipeline, consistent logging, tracking, and monitoring of pipelines and model performance to ensure consistent model performance and alert mechanisms for model drift.
Support data extraction and transformation for projects and users’ needs.
Review, support, improve, and run the platform, including the existing data platform/machine learning server, and environment management.
Provide support for data-related queries, extraction, and discrepancies.
Stay abreast of and analyze industry developments to identify areas of continuous improvement.

Job Requirements

Bachelor’s or Master’s degree in Computer Science, Artificial Intelligence, Machine Learning, or a related field.
2-4 years of experience in setting up a machine learning platform, developing and deploying machine learning models and AI solutions.
Familiarity with machine learning platforms, LLM, Lang Chain.
Proficiency in Python, SQL, and modern AI/ML algorithms, with experience in deploying solutions into production. Experience with GCP/Vertex AI is a plus.
Highly driven, proactive, and a strong team player. Excellent interpersonal, written, and verbal communication skills in English. Ability to multitask effectively and handle large amounts of data.

","hiringOrganization":{"@type":"Organization","name":"SGX Group","sameAs":"https://www.sgx.com"},"jobLocation":{"@type":"Place","address":{"@type":"PostalAddress","addressLocality":"Singapore, SG","addressCountry":"Singapore","addressRegion":"Asia/Pacific"}}}},{"@type":"ListItem","position":29,"item":{"@type":"JobPosting","title":"Staff Machine Learning Engineer – AI Research","datePosted":"2025-09-23","description":"

Job Description

Our AI Research team, reporting directly to the Chief AI Officer, is pioneering how cutting-edge machine learning can transform the way vehicles are designed, manufactured, and experienced. We are building the next generation of intelligent systems—integrating multimodal foundation models, generative AI, and robotics into real-world automotive innovation at global scale.

As a Staff Machine Learning Engineer on the AI Research team, you will serve as a founding member guiding GM’s most ambitious AI initiatives. You will participate in the design, prototyping, and deployment of state-of-the-art AI models with direct application to vehicle design, manufacturing operations, robotics, and simulation of physical systems. Beyond technical execution, you will shape and implement GM’s AI research agenda, join a world-class team of scientists and engineers, and represent GM in the global AI community.

What You’Ll Do

You will participate in a unique work environment which combines leading edge AI/ML research with immediate applications to exciting opportunities to make safer, more efficient cars. We have close working connections to world class engineers in the automotive design space to jointly develop novel applications of AI tools in this space.
Evaluate, prototype and implement impactful AI solutions to design and manufacturing operations at GM. Potential applications include the use of foundation models to large scale design tasks, using generative AI technologies for defining robotics tasks and the application of generative AI to interface with, and develop new technologies for the design and modeling physical systems.
Develop plans and execute projects to integrate AI into GM’s manufacturing, vehicle design, software development, customer support and other products and processes
Be on the forefront of AI models and architecture, making informed decisions on technology adoption and investment
Participating in the research, design, and prototyping of advanced AI models (foundation models, generative AI, multimodal architectures) applied to automotive and robotics domains.
Translate breakthrough AI research into scalable, production-ready systems across design, manufacturing, software, and customer experience.
Join a high-performing team of machine learning researchers and engineers.
Collaborate with product, design, and engineering leaders to identify high-impact AI opportunities.
Represent GM externally through publications, open-source contributions, patents, and participation in leading AI conferences.

Your Skills & Abilities (Required Qualifications)

PhD or equivalent in CS/EE
5+ years of experience in AI/ML research and applied development.
Deep expertise in modern ML architectures (transformers, generative AI, multimodal systems).
Proven track record of leading AI projects from research to production at scale.
Strong programming skills in Python and proficiency in one or more systems languages (C++/Go/Java).
Experience deploying AI systems on cloud-based GPUs/TPUs (AWS, Azure, GCP).
Recognized thought leader in the AI/ML community with demonstrated impact (research breakthroughs, patents, or widely adopted technologies).
Exceptional ability to mentor, influence, and collaborate across technical and business teams.

What Will Give You A Competitive Edge (Preferred Qualifications)

Demonstrated expertise in developing and training multimodal foundation models
Demonstrated research impact in AI/ML technologies either through important publications in first tier conferences or demonstrated contribution to industry leading systems.

This role is categorized as hybrid. This means the successful candidate is expected to report to the MTV office three times per week or any other frequency dictated by the business.

Compensation: The compensation information is a good faith estimate only. It is based on what a successful applicant might be paid in accordance with applicable state laws. The compensation may not be representative for positions located outside of New York, Colorado, California, or Washington.

The salary range for this role is 198,000 to 250,000. The actual base salary a successful candidate will be offered within this range will vary based on factors relevant to the position.
Bonus Potential: An incentive pay program offers payouts based on company performance, job level, and individual performance.
Benefits: GM offers a variety of health and wellbeing benefit programs. Benefit options include medical, dental, vision, Health Savings Account, Flexible Spending Accounts, retirement savings plan, sickness and accident benefits, life insurance, paid vacation & holidays, tuition assistance programs, employee assistance program, GM vehicle discounts and more.

Company Vehicle: Upon successful completion of a motor vehicle report review, you will be eligible to participate in a company vehicle evaluation program, through which you will be assigned a General Motors vehicle to drive and evaluate.

Note: program participants are required to purchase/lease a qualifying GM vehicle every four years unless one of a limited number of exceptions applies.

Relocation: This job may be eligible for relocation benefits.

#Li-Cx1

About Gm

Our vision is a world with Zero Crashes, Zero Emissions and Zero Congestion and we embrace the responsibility to lead the change that will make our world better, safer and more equitable for all.

Why Join Us

We believe we all must make a choice every day – individually and collectively – to drive meaningful change through our words, our deeds and our culture. Every day, we want every employee to feel they belong to one General Motors team.

Benefits Overview

From day one, we're looking out for your well-being–at work and at home–so you can focus on realizing your ambitions. Learn how GM supports a rewarding career that rewards you personally by visiting Total Rewards resources.

Non-Discrimination and Equal Employment Opportunities (U.S.)

General Motors is committed to being a workplace that is not only free of unlawful discrimination, but one that genuinely fosters inclusion and belonging. We strongly believe that providing an inclusive workplace creates an environment in which our employees can thrive and develop better products for our customers.

All employment decisions are made on a non-discriminatory basis without regard to sex, race, color, national origin, citizenship status, religion, age, disability, pregnancy or maternity status, sexual orientation, gender identity, status as a veteran or protected veteran, or any other similarly protected status in accordance with federal, state and local laws.

We encourage interested candidates to review the key responsibilities and qualifications for each role and apply for any positions that match their skills and capabilities. Applicants in the recruitment process may be required, where applicable, to successfully complete a role-related assessment(s) and/or a pre-employment screening prior to beginning employment. To learn more, visit How we Hire.

Accommodations

General Motors offers opportunities to all job seekers including individuals with disabilities. If you need a reasonable accommodation to assist with your job search or application for employment, email us or call us at 800-865-7580. In your email, please include a description of the specific accommodation you are requesting as well as the job title and requisition number of the position for which you are applying.

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The Company

PayPal has been revolutionizing commerce globally for more than 25 years. Creating innovative experiences that make moving money, selling, and shopping simple, personalized, and secure, PayPal empowers consumers and businesses in approximately 200 markets to join and thrive in the global economy.

We operate a global, two-sided network at scale that connects hundreds of millions of merchants and consumers. We help merchants and consumers connect, transact, and complete payments, whether they are online or in person. PayPal is more than a connection to third-party payment networks. We provide proprietary payment solutions accepted by merchants that enable the completion of payments on our platform on behalf of our customers.

We offer our customers the flexibility to use their accounts to purchase and receive payments for goods and services, as well as the ability to transfer and withdraw funds. We enable consumers to exchange funds more safely with merchants using a variety of funding sources, which may include a bank account, a PayPal or Venmo account balance, PayPal and Venmo branded credit products, a credit card, a debit card, certain cryptocurrencies, or other stored value products such as gift cards, and eligible credit card rewards. Our PayPal, Venmo, and Xoom products also make it safer and simpler for friends and family to transfer funds to each other. We offer merchants an end-to-end payments solution that provides authorization and settlement capabilities, as well as instant access to funds and payouts. We also help merchants connect with their customers, process exchanges and returns, and manage risk. We enable consumers to engage in cross-border shopping and merchants to extend their global reach while reducing the complexity and friction involved in enabling cross-border trade.

Our beliefs are the foundation for how we conduct business every day. We live each day guided by our core values of Inclusion, Innovation, Collaboration, and Wellness. Together, our values ensure that we work together as one global team with our customers at the center of everything we do – and they push us to ensure we take care of ourselves, each other, and our communities.

Job Summary:

This job will design, develop, and implement machine learning models and algorithms to solve complex problems. You will work closely with data scientists, software engineers, and product teams to enhance services through innovative AI/ML solutions. Your role will involve building scalable ML pipelines, ensuring data quality, and deploying models into production environments to drive business insights and improve customer experiences.

Job Description:

Essential Responsibilities:

Develop and optimize machine learning models for various applications.
Preprocess and analyze large datasets to extract meaningful insights.
Deploy ML solutions into production environments using appropriate tools and frameworks.
Collaborate with cross-functional teams to integrate ML models into products and services.
Monitor and evaluate the performance of deployed models.

Minimum Qualifications:

Minimum of 5 years of relevant work experience and a Bachelor's degree or equivalent experience.
Experience with ML frameworks like TensorFlow, PyTorch, or scikit-learn.
Familiarity with cloud platforms (AWS, Azure, GCP) and tools for data processing and model deployment.
Several years of experience in designing, implementing, and deploying machine learning models.

Preferred Qualification:

Subsidiary:

PayPal

Travel Percent:

PayPal does not charge candidates any fees for courses, applications, resume reviews, interviews, background checks, or onboarding. Any such request is a red flag and likely part of a scam. To learn more about how to identify and avoid recruitment fraud please visit https://careers.pypl.com/contact-us.

For the majority of employees, PayPal's balanced hybrid work model offers 3 days in the office for effective in-person collaboration and 2 days at your choice of either the PayPal office or your home workspace, ensuring that you equally have the benefits and conveniences of both locations.

Our Benefits:

At PayPal, we’re committed to building an equitable and inclusive global economy. And we can’t do this without our most important asset—you. That’s why we offer benefits to help you thrive in every stage of life. We champion your financial, physical, and mental health by offering valuable benefits and resources to help you care for the whole you.

We have great benefits including a flexible work environment, employee shares options, health and life insurance and more. To learn more about our benefits please visit https://www.paypalbenefits.com.

Who We Are:

Click Here to learn more about our culture and community.

Commitment to Diversity and Inclusion

PayPal provides equal employment opportunity (EEO) to all persons regardless of age, color, national origin, citizenship status, physical or mental disability, race, religion, creed, gender, sex, pregnancy, sexual orientation, gender identity and/or expression, genetic information, marital status, status with regard to public assistance, veteran status, or any other characteristic protected by federal, state, or local law. In addition, PayPal will provide reasonable accommodations for qualified individuals with disabilities. If you are unable to submit an application because of incompatible assistive technology or a disability, please contact us at paypalglobaltalentacquisition@paypal.com.

Belonging At Paypal:

Our employees are central to advancing our mission, and we strive to create an environment where everyone can do their best work with a sense of purpose and belonging. Belonging at PayPal means creating a workplace with a sense of acceptance and security where all employees feel included and valued. We are proud to have a diverse workforce reflective of the merchants, consumers, and communities that we serve, and we continue to take tangible actions to cultivate inclusivity and belonging at PayPal.

Any general requests for consideration of your skills, please Join our Talent Community.

We know the confidence gap and imposter syndrome can get in the way of meeting spectacular candidates. Please don’t hesitate to apply.

","hiringOrganization":{"@type":"Organization","name":"PayPal","sameAs":"https://www.paypal.com/"},"jobLocation":{"@type":"Place","address":{"@type":"PostalAddress","addressLocality":"SGP - Central Singapore - Corp - Temasek Blvd","addressCountry":"Singapore","addressRegion":"Asia/Pacific"}}}},{"@type":"ListItem","position":31,"item":{"@type":"JobPosting","title":"Computer Vision / Machine Learning Engineer","datePosted":"2025-09-22","description":"About the Role
We're looking for an experienced Computer Vision/Machine Learning Engineer to join our team, where you will apply your expertise to solve real-world computer vision problems. You'll play a key role in building, deploying, and integrating ML solutions into large-scale software systems, working collaboratively with all teams to help define the technical roadmap for our products. This position is ideal for someone who wants to work on critical software that has a real-world impact.\n

Responsibilities

Apply machine learning and computer vision techniques to add new analytical capabilities to our products, as well as enabling modern CV processing within our 3D reconstruction pipeline
Design, build, train, and experiment with ML models using PyTorch
Deploy ML models into production and integrate them into a large C++ codebase
Write and oversee code quality, testing, development standards, and best practices, ensuring robust, clean, and maintainable codebases
Work collaboratively with the Reveal team to define and execute the technical roadmap for current and future products
Contribute to technical documentation, design reviews, and code reviews to ensure maintainability and knowledge sharing
Stay up to date with the latest research and industry trends in CV, ML, and 3D data processing, applying relevant advancements where appropriate
Debug, identify root causes, and implement and test fixes for problems
Develop technical materials from conceptual ideas

Requirements

3-5 years of experience applying machine learning to solve real-world computer vision problems
Must be eligible to obtain and maintain a U.S. Top Secret security clearance
Deep understanding of computer vision fundamentals, including classical and ML-based approaches
Experience building, training, and experimenting with models using PyTorch
Experience deploying ML models to production environments
Familiarity with the ONNX framework
Experience with and willingness to work on software implementation and integration of ML solutions into large codebases
Experience with C++ and Python development in Linux or other command-line-based environments
Solid understanding of linear algebra
Ability to quickly understand and navigate complex systems and established codebases
Familiarity with representations of 3D data, such as point clouds, polygonal meshes, and depth maps, and algorithms for generating and processing them
Ability to quickly understand and navigate complex systems and established code bases
A desire to work on critical software that has a real-world impact

Nice To Haves

Working knowledge of classical 3D Computer Vision concepts such as camera models, stereo vision, camera calibration, SfM, SLAM
Familiarity with modern 3D CV advancements such as neural rendering techniques (NERFs, Gaussian Splatting), and related approaches for 3D reconstruction and scene representation
Experience building software solutions involving significant amounts of data processing and analysis

Compensation

Salary + Equity
Salary is determined by the applicant's experience, knowledge, skills, abilities, internal equity, and alignment with market data.

Benefits

Medical, Dental, Vision coverage
HSA/FSA options
Parental Leave
401(k): 200% match for the first 6% contributed
Unlimited Paid Time Off
Home Office Stipend

About Reveal TechnologyFounded in 2019, Reveal is a dynamic startup revolutionizing field operations by providing software tools and insights to individuals in remote, disconnected, and extreme environments. Our products include Farsight, a 3D processing and mission planning tool, and Identifi, which enables secure and rapid identity verification. Reveal is deeply committed to supporting defense, security, and safety missions. Having recently closed a $30M Series B funding round, we're growing our team to meet expanding demands and opportunities.
This position will be open on or our website until it is successfully filled. To submit your application, please click the “Apply” button and follow the steps as directed.
Proof of identity and eligibility to work in the United States is required for all hires.
All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, or status as a protected veteran.
Note: This job posting is intended for direct applicants only. We do not accept any unsolicited applications and request no outside recruiters contact us regarding this role.","hiringOrganization":{"@type":"Organization","name":"Reveal Technology","sameAs":"https://www.revealtech.ai"},"jobLocation":{"@type":"Place","address":{"@type":"PostalAddress","addressLocality":"Remote, USA","addressCountry":"United States","addressRegion":"North America"}}}},{"@type":"ListItem","position":32,"item":{"@type":"JobPosting","title":"Senior Machine Learning Engineer (Modeling), Risk","datePosted":"2025-09-22","description":"

It all started with an idea at Block in 2013. Initially built to take the pain out of peer-to-peer payments, Cash App has gone from a simple product with a single purpose to a dynamic ecosystem, developing unique financial products, including Afterpay/Clearpay, to provide a better way to send, spend, invest, borrow and save to our 50+ million monthly active customers. We want to redefine the world's relationship with money to make it more relatable, instantly available, and universally accessible.

\n\n

Today, Cash App has thousands of employees working globally across office and remote locations, with a culture geared toward innovation, collaboration and impact. We've been a distributed team since day one, and many of our roles can be done remotely from the countries where Cash App operates. No matter the location, we tailor our experience to ensure our employees are creative, productive, and happy.

The Role

Machine Learning is an integral part of how we at Cash App design products, operate, and pursue our mission to serve the unbanked as well as disrupt traditional financial institutions. Our massive scale and deep trove of transaction data create an endless number of opportunities to use ML and AI methods to better understand our customers and offer new products and experiences that can improve their lives. We are a highly creative group that prefers to solve problems from first principles; we move quickly, make incremental changes, and deploy to production every day.

As part of the Risk ML team, you will build machine learning models that detect fraudulent activity in real time and help keep our customers safe and secure. You will experiment with state-of-the-art algorithms to drive down false positives, collaborate on new product features to drive fraud losses down, use any and every dataset at your disposal to analyse emerging fraud patterns, engineer new features for risk models, and deploy robust models to take action on bad activity in real time.

This role can work remotely from anywhere in Australia or New Zealand, or from our offices in Melbourne, Sydney and Auckland.

You Will

Be responsible for building machine learning models to detect and act against fraudulent activity, as well as researching emerging fraud patterns, and leading and participating in cross-functional initiatives to tackle problems.
Collaborate cross-functionally with our engineering, product, and operations teams located across Australia and the United States (particularly Melbourne and San Francisco) to keep our customers and their money safe.
Work closely with the ML Engineering teams who build the systems that allow our models to operate at scale and in real time.
Contribute to the growth of our modelling capabilities through mentoring and supporting fellow modellers
Exercise a high level of autonomy and responsibility, own your solutions from design through to operation

You Have

Bachelor's degree in a quantitative field such as Mathematics/Statistics/Physics or Machine Learning. Masters or PhD preferred
3+ years of experience in machine learning, artificial intelligence, or a related field
Strong knowledge of machine learning algorithms and data analysis techniques
Excellent problem-solving skills and attention to detail
Strong communication skills, with the ability to explain complex concepts to non-technical stakeholders

Technologies We Use And Teach

Python (NumPy, Pandas, sklearn, xgboost, TensorFlow, keras, etc.)
MySQL, Snowflake, Tableau, Mode
GCP/AWS

Use of AI in Our Hiring Process

We may use automated AI tools to evaluate job applications for efficiency and consistency. These tools comply with local regulations, including bias audits, and we handle all personal data in accordance with state and local privacy laws.

Every benefit we offer is designed with one goal: empowering you to do the best work of your career while building the life you want. Remote work, medical insurance, flexible time off, retirement savings plans, and modern family planning are just some of our offering. Check out our other benefits at Block.

Block, Inc. (NYSE: XYZ) builds technology to increase access to the global economy. Each of our brands unlocks different aspects of the economy for more people. Square makes commerce and financial services accessible to sellers. Cash App is the easy way to spend, send, and store money. Afterpay is transforming the way customers manage their spending over time. TIDAL is a music platform that empowers artists to thrive as entrepreneurs. Bitkey is a simple self-custody wallet built for bitcoin. Proto is a suite of bitcoin mining products and services. Together, we’re helping build a financial system that is open to everyone.

Privacy Policy

","hiringOrganization":{"@type":"Organization","name":"Block","sameAs":"https://block.xyz/"},"jobLocation":{"@type":"Place","address":{"@type":"PostalAddress","addressLocality":"Melbourne, Australia","addressCountry":"Australia","addressRegion":"Asia/Pacific"}}}},{"@type":"ListItem","position":33,"item":{"@type":"JobPosting","title":"Co-op - Machine Learning Engineer (Spanish/Portuguese)","datePosted":"2025-09-22","description":"At Lendbuzz, we believe financial opportunity should be more personalized and fair. We develop innovative technologies that provide underserved and overlooked borrowers with better access to credit. From our employees to our dealers, partners, and borrowers, we’ve built a company and a culture around a resolute belief in the promise and power of diversity. We value independent and critical thinking.
We are seeking an enthusiastic Machine Learning Co-op to join our team, focusing on our sales and collection AI chatbot projects within our Language Understanding and Semantic Analysis group. Ideal candidates should be proficient in Spanish or Portuguese, eager to explore the intricacies of the auto loan industry, and interested in building real-world applications of Large Language Models (LLMs). You will gain hands-on experience with large-scale data annotation, data cleaning, multilingual model evaluation, and product design.\n

Key Responsibilities:

Annotate chat data from sales-dealers and customers to train AI chatbots
Develop and refine prompts and Retrieval-Augmented Generation (RAG) technique cvg cant es to enhance the performance of zero-shot and few-shot language models (LLMs)
Assess the needs of dealers and customers, and implement AI chatbot functionalities to address those needs
Fine-tune language models as time permits and based on the availability of annotated data

Requirements:

Proficiency in either Spanish or Portuguese (spoken and written) is required
Pursuing a Bachelor’s degree in Computer Science or a related field, pursuing a M.S in Computer Science or a related field preferred (graduation date of December 2026 or later)
Coursework or experience in Data Structures, Algorithms, Linear Algebra, Probability, and foundational Machine Learning and Artificial Intelligence concepts
Familiarity with Python and its data analysis libraries
Strong grasp of core CS and ML concepts
Interview process will include questions on coursework, coding, probability, machine learning, and Linux fundamentals
Able to work 3-4 days in our downtown Boston office full time from January-August 2026

We believe:
Diversity is a competitive advantage. We celebrate our differences, and are better when we have a variety of experiences, viewpoints, and backgrounds.
Compassion is a strength. We care about our customers and look to build long-term relationships with them.
Simplicity is a key feature. We work hard to make our forms and processes as painless and intuitive as possible.
Honesty and transparency are non negotiable. We incorporate these traits in all of our interactions.
Financial opportunity belongs to everyone. We work every day to improve lives by extending this opportunity.
If you believe these things too then we would love to hear from you!","hiringOrganization":{"@type":"Organization","name":"Lendbuzz","sameAs":"https://www.lendbuzz.com/"},"jobLocation":{"@type":"Place","address":{"@type":"PostalAddress","addressLocality":"Boston, MA","addressCountry":"United States","addressRegion":"North America"}}}},{"@type":"ListItem","position":34,"item":{"@type":"JobPosting","title":"Machine Learning Engineer, AI Decisioning","datePosted":"2025-09-22","description":"

About Hightouch

Hightouch’s mission is to empower everyone to take action on their data. Hundreds of companies, including Autotrader, Calendly, Cars.com, Monday.com, and PetSmart, trust Hightouch to power their growth.

We pioneered the Composable Customer Data Platform (CDP), which lets companies use their own data warehouse to collect, prepare, and activate customer data for marketing personalization and business operations. Our new AI Decisioning platform goes a step further, allowing marketers to set goals and guardrails that AI agents can then use to personalize 1:1 customer interactions. Traditionally, only technical teams had the skills to access and use customer data. With Hightouch, every business user can deliver personalized customer experiences, optimize performance marketing, and move faster by leveraging data and AI across their organization.

Our team focuses on making a meaningful impact for our customers. We approach challenges with a first-principles mindset, move quickly and efficiently, and treat each other with compassion and kindness. We look for team members who are strong communicators, have a growth mindset, and are motivated and persistent in achieving our goals.

What else? We’re based in San Francisco but have team members all over the world. Our Series C put us at a $1.2B valuation, and we are backed by leading investors such as Sapphire Ventures, Amplify Partners, ICONIQ Growth, Bain Capital Ventures, Y-Combinator, and Afore Capital.

About The Role

We’re looking to hire a machine learning engineer as we expand our data activation products to include an intelligence layer. While hundreds of companies use Hightouch today to sync data into their SaaS systems to automate and improve operations, there’s a lot of surface area we haven’t touched in helping companies figuring out which customers to message, what content to put in messages, and when to send messages. A lot of this work today is done manually through intuition and guesswork, and we believe that adding machine learning could have a step function impact for our customers. And given our access to data warehouses and databases, Hightouch is perfectly placed to make use of a company’s customer data in building a powerful intelligence layer.

Some of the problems we’ll be working on include:

Personalization and Product Recommendation: There are often many options for what content a company could message a user with, including which products to show from catalogues. Given this large state space, how can Hightouch help personalize messages with the most relevant content for each user?
Automated Experimentation: Helping companies intelligently navigate and automate experiments across the extensive number of options for messaging customers.
Predictive Audiences: Building models to predict which users are most likely to convert, churn, or take desired actions.
Content Generation: Particularly with recent advances in LLMs, how can we help marketers generate text, images, and creatives that are compelling to their customers?
Budget Optimization: Helping companies assess which marketing spend is driving the most incremental conversions, and where the marginal CAC is lowest.

As an early machine learning engineer, you will help build comprehensive solutions to the above domains from scratch. Responsibilities will be highly varied and include working on customer research, problem definition, predictive modeling, machine learning infrastructure, and partnering with customers.

We are looking for talented, intellectually curious, and motivated individuals who are interested in tackling the problems above. This is a senior role, but we focus on impact and potential for growth more than years of experience. The salary range for this position is $200,000 - $260,000 USD per year, which is location independent in accordance with our remote-first policy.

Interview Process

Our interview process focuses on evaluating fit for the most important dimensions of the role: product sense, ability to architect backend and distributed systems, and alignment with Hightouch’s values. Notably, we don’t do any programming interviews as we believe they are low signal to noise and aren’t a good evaluation mechanism.

Intro Call [15-30m]: Introductory call with either a member of our recruiting team or the hiring manager to get to know each other and see if the role could be a good mutual fit.
System Design Screen [45m]: Designing a data processing feature end-to-end.
Machine Learning Modeling Interview [90m]: Designing a predictive model end-to-end, including data collection and preparation, model training and evaluation, and what systems would be needed to run the model in production.
System Design Interview [90m]: Work with the interviewer to architect a system at a conceptual level. The problem will be at a pretty high level - and have both product and customer requirements as well as technical.
Hiring Manager Interview [30m]: Chat with hiring manager about past experiences and future operating preferences to assess fit on company values and operating principles.

","hiringOrganization":{"@type":"Organization","name":"Hightouch","sameAs":"https://hightouch.com/"},"jobLocation":{"@type":"Place","address":{"@type":"PostalAddress","addressLocality":"Remote (North America)"}}}},{"@type":"ListItem","position":35,"item":{"@type":"JobPosting","title":"Machine Learning Engineer - New Grad 2026","datePosted":"2025-09-22","description":"

#Teamnextdoor

Nextdoor (NYSE: NXDR) is the essential neighborhood network. Neighbors, public agencies, and businesses use Nextdoor to connect around local information that matters in more than 340,000 neighborhoods across 11 countries. Nextdoor builds innovative technology to foster local community, share important news, and create neighborhood connections at scale. Download the app and join the neighborhood at nextdoor.com.

Meet Your Future Neighbors

At Nextdoor, Machine Learning is one of the most critical teams we are growing. ML is transforming our product through personalization, driving significant impact across various platform components, including newsfeed, notifications, ad relevance, connections, search, and trust. Our machine learning team is lean but hungry to drive even more impact and make Nextdoor the neighborhood hub for local exchange. ML will be an integral part of making Nextdoor valuable to our members. We also believe that ML should be ethical and encourage healthy habits and interaction, not addictive behavior. We are looking for great machine learning engineers who believe in the power of the local community to empower our members to make their communities great places to live.

At Nextdoor, we offer a warm and inclusive work environment that embraces a hybrid employment model, blending an in-office presence and work-from-home experience for our valued employees.

The Impact You’Ll Make

You will be part of an avid and impactful team building data-intensive products, working with data and features, building machine learning models, and sharing insights around data and experiments. You will be working closely with the product team and the Data Science team on a daily basis.

Build and iterate on ML-driven products to foster creativity, discovery, and engagement on Nextdoor
Develop personalized content and user recommendation systems that millions of users rely on daily
Run and analyze live user-facing experiments to iterate on model quality
Collaborate with other engineers and data scientists to create optimal experiences on the platform
Participate in in-person Nextdoor events such as trainings, off-sites, volunteer days, and team building exercises
Build in-person relationships with team members and contribute to Nextdoor’s company culture

We have MLE positions across multiple tracks, including Feed, Notifications, Ads, Network Growth, Knowledge Graph, and ML Platform.

What You’Ll Bring To The Team

Master’s Degree or Ph.D. in Computer Science, Applied Math, Statistics, or a related field, graduating in December 2025
Deep understanding of machine learning concepts (e.g. deep learning) and applications (e.g. recommender systems, knowledge graph)
Internship in machine learning engineering in a related field (e.g. social networking, e-commerce)
Strong programming skills in Python or Java
Effective communication and collaboration skills
Passion for Nextdoor’s mission and purpose
Bonus Points - Industry experience of applying machine learning at scale
Eagerness to explore and apply AI and emerging technologies to reimagine how work gets done

Rewards

Compensation, benefits, perks, and recognition programs at Nextdoor come together to create our total rewards package. Compensation will vary depending on your relevant skills, experience, and qualifications. Compensation may also vary by geography.

The starting salary for this role is expected to be $150,000 to $175,000 on an annualized basis, or potentially greater in the event that your 'level' of proficiency exceeds the level expected for the role.

We also expect to award a meaningful equity grant for this role. With equal quarterly vesting, your first vest date would be within the first 3 months of your start date.

Perks & Benefits

We’ve got you covered! We are dedicated to supporting your personal and professional growth with a comprehensive benefits package that includes:

Access to benefits (including mental health benefits, commuter benefits, wellness benefits, gender affirming care, etc)
Flexible paid time off
Dedicated volunteer days
Stocked micro-kitchens and lunches at our offices
Ability to join any of our Employee Resource Groups (ERGs)

At Nextdoor, we empower our employees to build stronger local communities. To create a platform where all feel welcome, we want our workforce to reflect the diversity of the neighbors we seek to serve. We encourage everyone interested in our purpose to apply. We do not discriminate on the basis of race, gender, religion, sexual orientation, age, or any other trait that unfairly targets a group of people. In accordance with the Fair Chance Ordinance, we always consider qualified applicants with arrest and conviction records.

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\n\n

Job Responsibilities

\n\n

You will contribute to design and drive the development of robust scalable architectures and infrastructure for deploying and managing machine learning (ML) applications, ensuring high availability, performance and security.
You will collaborate with data scientists and engineers to translate business needs into effective and efficient ML systems and applications.
You will own the development and maintenance of core functionalities within ML applications, including ML pipelines, model training and deployment, and monitoring and evaluation.
You will drive the functional stream of work by providing technical expertise, handling team discussions and ensuring timely delivery of assigned tasks.
You will stay ahead of the curve by actively exploring and implementing the latest tools, frameworks and offerings in the ML landscape.
You will facilitate collaborative problem solving within the team by actively listening, communicating effectively and mentoring other engineers.
You will contribute to the development and execution of the team's overall ML strategy, aligning technical capabilities with business objectives.
You will proactively identify and address challenges related to ML systems and applications, proposing solutions and implementing improvements.

\n\n

Job Qualifications

\n\n

Technical Skills

\n\n

An advanced English level is required.
You must have a strong experience with LLM and AI.
You have experience in writing clean, maintainable and testable code, demonstrating attention to refactoring and readability of the code.
You are proficient in scripting languages such as Python or Shell for automation and task streamlining.
You have knowledge of distributed systems and scalable architectures to handle large-scale ML applications.
You have experience with building, deploying, and maintaining ML systems using relevant ML techniques and platforms, i.e.: Scikit-learn, Tensorflow, MLFlow, Kubeflow, Pytorch.
You have experience with building, deploying and maintaining ML systems and experience with application of MLOps principles and CI/CD to ML.
You have experience in machine learning engineering and data science, are familiar with key ML concepts, algorithms and frameworks, and understand ML model lifecycles.
You have experience with designing and operating the infrastructure required to run different types of ML training and serving workloads, i.e.: on-premise vs. cloud infrastructure, infrastructure as code, monitoring, etc.
You have hands-on experience with on-premise and cloud services for building and deploying ML pipelines, i.e.: Azure, AWS, GCP or Databricks and associated ML managed services.

\n\n

Professional Skills

\n\n

You understand the importance of stakeholder management and can easily liaise between clients and other key stakeholders throughout projects, ensuring buy-in and gaining trust along the way.
You are resilient in ambiguous situations and can adapt your role to approach challenges from multiple perspectives.
You don’t shy away from risks or conflicts, instead you take them on and skillfully manage them.
You are eager to coach, mentor and motivate others and you aspire to influence teammates to take positive action and accountability for their work.
You enjoy influencing others and always advocate for technical excellence while being open to change when needed.

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Other Things To Know

\n\n

Learning & Development

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\n\n\n

About Thoughtworks

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Thoughtworks is a dynamic and inclusive community of bright and supportive colleagues who are revolutionizing tech. As a leading technology consultancy, we’re pushing boundaries through our purposeful and impactful work. For 30+ years, we’ve delivered extraordinary impact together with our clients by helping them solve complex business problems with technology as the differentiator. Bring your brilliant expertise and commitment for continuous learning to Thoughtworks. Together, let’s be extraordinary.

\n\n

#Li-Remote

See here our AI policy.

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\n\n

Job Responsibilities

\n\n

You will contribute to design and drive the development of robust scalable architectures and infrastructure for deploying and managing machine learning (ML) applications, ensuring high availability, performance and security.
You will collaborate with data scientists and engineers to translate business needs into effective and efficient ML systems and applications.
You will own the development and maintenance of core functionalities within ML applications, including ML pipelines, model training and deployment, and monitoring and evaluation.
You will drive the functional stream of work by providing technical expertise, handling team discussions and ensuring timely delivery of assigned tasks.
You will stay ahead of the curve by actively exploring and implementing the latest tools, frameworks and offerings in the ML landscape.
You will facilitate collaborative problem solving within the team by actively listening, communicating effectively and mentoring other engineers.
You will contribute to the development and execution of the team's overall ML strategy, aligning technical capabilities with business objectives.
You will proactively identify and address challenges related to ML systems and applications, proposing solutions and implementing improvements.

\n\n

Job Qualifications

\n\n

Technical Skills

\n\n

An advanced English level is required.
You must have a strong experience with LLM and AI.
You have experience in writing clean, maintainable and testable code, demonstrating attention to refactoring and readability of the code.
You are proficient in scripting languages such as Python or Shell for automation and task streamlining.
You have knowledge of distributed systems and scalable architectures to handle large-scale ML applications.
You have experience with building, deploying, and maintaining ML systems using relevant ML techniques and platforms, i.e.: Scikit-learn, Tensorflow, MLFlow, Kubeflow, Pytorch.
You have experience with building, deploying and maintaining ML systems and experience with application of MLOps principles and CI/CD to ML.
You have experience in machine learning engineering and data science, are familiar with key ML concepts, algorithms and frameworks, and understand ML model lifecycles.
You have experience with designing and operating the infrastructure required to run different types of ML training and serving workloads, i.e.: on-premise vs. cloud infrastructure, infrastructure as code, monitoring, etc.
You have hands-on experience with on-premise and cloud services for building and deploying ML pipelines, i.e.: Azure, AWS, GCP or Databricks and associated ML managed services.

\n\n

Professional Skills

\n\n

You understand the importance of stakeholder management and can easily liaise between clients and other key stakeholders throughout projects, ensuring buy-in and gaining trust along the way.
You are resilient in ambiguous situations and can adapt your role to approach challenges from multiple perspectives.
You don’t shy away from risks or conflicts, instead you take them on and skillfully manage them.
You are eager to coach, mentor and motivate others and you aspire to influence teammates to take positive action and accountability for their work.
You enjoy influencing others and always advocate for technical excellence while being open to change when needed.

\n\n\n

Other Things To Know

\n\n

Learning & Development

\n\n

\n\n\n

About Thoughtworks

\n\n

#Li-Remote

See here our AI policy.

","hiringOrganization":{"@type":"Organization","name":"Thoughtworks","sameAs":"https://www.thoughtworks.com/"},"jobLocation":{"@type":"Place","address":{"@type":"PostalAddress","addressLocality":"Lima","addressCountry":"Peru","addressRegion":"South America"}}}},{"@type":"ListItem","position":38,"item":{"@type":"JobPosting","title":"Senior Machine Learning Engineer","datePosted":"2025-09-22","description":"

\n\n

Job Responsibilities

\n\n

You will contribute to design and drive the development of robust scalable architectures and infrastructure for deploying and managing machine learning (ML) applications, ensuring high availability, performance and security.
You will collaborate with data scientists and engineers to translate business needs into effective and efficient ML systems and applications.
You will own the development and maintenance of core functionalities within ML applications, including ML pipelines, model training and deployment, and monitoring and evaluation.
You will drive the functional stream of work by providing technical expertise, handling team discussions and ensuring timely delivery of assigned tasks.
You will stay ahead of the curve by actively exploring and implementing the latest tools, frameworks and offerings in the ML landscape.
You will facilitate collaborative problem solving within the team by actively listening, communicating effectively and mentoring other engineers.
You will contribute to the development and execution of the team's overall ML strategy, aligning technical capabilities with business objectives.
You will proactively identify and address challenges related to ML systems and applications, proposing solutions and implementing improvements.

\n\n

Job Qualifications

\n\n

Technical Skills

\n\n

An advanced English level is required.
You must have a strong experience with LLM and AI.
You have experience in writing clean, maintainable and testable code, demonstrating attention to refactoring and readability of the code.
You are proficient in scripting languages such as Python or Shell for automation and task streamlining.
You have knowledge of distributed systems and scalable architectures to handle large-scale ML applications.
You have experience with building, deploying, and maintaining ML systems using relevant ML techniques and platforms, i.e.: Scikit-learn, Tensorflow, MLFlow, Kubeflow, Pytorch.
You have experience with building, deploying and maintaining ML systems and experience with application of MLOps principles and CI/CD to ML.
You have experience in machine learning engineering and data science, are familiar with key ML concepts, algorithms and frameworks, and understand ML model lifecycles.
You have experience with designing and operating the infrastructure required to run different types of ML training and serving workloads, i.e.: on-premise vs. cloud infrastructure, infrastructure as code, monitoring, etc.
You have hands-on experience with on-premise and cloud services for building and deploying ML pipelines, i.e.: Azure, AWS, GCP or Databricks and associated ML managed services.

\n\n

Professional Skills

\n\n

You understand the importance of stakeholder management and can easily liaise between clients and other key stakeholders throughout projects, ensuring buy-in and gaining trust along the way.
You are resilient in ambiguous situations and can adapt your role to approach challenges from multiple perspectives.
You don’t shy away from risks or conflicts, instead you take them on and skillfully manage them.
You are eager to coach, mentor and motivate others and you aspire to influence teammates to take positive action and accountability for their work.
You enjoy influencing others and always advocate for technical excellence while being open to change when needed.

\n\n\n

Other Things To Know

\n\n

Learning & Development

\n\n

\n\n\n

About Thoughtworks

\n\n

#Li-Remote

See here our AI policy.

","hiringOrganization":{"@type":"Organization","name":"Thoughtworks","sameAs":"https://www.thoughtworks.com/"},"jobLocation":{"@type":"Place","address":{"@type":"PostalAddress","addressLocality":"Santiago","addressCountry":"Chile","addressRegion":"South America"}}}},{"@type":"ListItem","position":39,"item":{"@type":"JobPosting","title":"Senior Machine Learning Engineer, Ads Foundation Modeling","datePosted":"2025-09-22","description":"

The opportunity
At Unity, we’re committed to building a culture that fosters collaboration and innovation. Within our fast-paced environment, we’re tackling complex challenges that drive meaningful impact for creators and users across our ecosystem.

Our Foundation Modeling team plays a central role in this effort by developing state-of-the-art conversion rate (CVR) prediction and market price models that power our ad ranking and recommendation systems. These models help advertisers reach the right users at the right time by accurately estimating engagement and conversion likelihood. By leveraging large-scale behavioral data, creative features, and contextual signals, we continuously improve the relevance and accuracy of our predictions. This drives key outcomes such as higher user engagement, stronger conversion performance, and better return on ad spend — enabling advertisers to achieve their goals while delivering a better experience for users.

We are seeking a highly skilled Senior ML Engineer to drive state-of-the-art bidding optimization systems that enable efficient budget pacing, goal-aligned automated strategies, continual improvement through experimentation, and sustainable growth for Unity Ads.

What you'll be doing

Design, implement, and maintain high-performance CTR and CVR prediction models that power ad ranking and recommendation systems.
Build and refine systems for creative understanding and user behavior modeling, enabling more accurate and context-aware engagement predictions.
Ensure model quality and reliability by continuously monitoring performance, calibrating predictions, and addressing data drift or delayed feedback.
Actively participate and work with other leads to set the long term direction for the team, plan and oversee engineering designs and project execution.
Effectively communicate complex technical concepts to non-engineering stakeholders.

What we're looking for

Advanced degree (MS or Ph.D.) in Computer Science, Machine Learning, Statistics, related field, or equivalent practical experience.
5+ years of hands-on experience building and operating large-scale Ads delivery and optimization systems.
3+ years of experience building CTR/CVR systems, content understanding, or behavior modeling systems.
Significant experience in one or more general-purpose programming languages like Python, Go, Scala, C++ or similar.
Knowledge of metric design, experimentation methodologies, and large-scale data analysis.

You might also have

Experience designing and productionizing optimization algorithms in an ad serving platform and/or other marketplaces.
Experience with state-of-the-art control systems, reinforcement learning algorithms.

Additional Information

International relocation support is not available for this position.
Life at Unity
We offer a wide range of benefits designed to support employees' well-being and work-life balance. You can read more about them on our career page.

\n\n

Unity [NYSE: U] is the leading platform to create and grow games and interactive experiences. Creators, ranging from game developers to artists, architects, automotive designers, infrastructure experts, filmmakers, and more, use Unity to bring their imaginations to life across multiple platforms, from mobile, PC, and console, to spatial computing.

As of the third quarter of 2024, more than 70% of the top 1,000 mobile games were made with Unity, and in 2024, Made with Unity applications had an average of 3.7 billion downloads per month. For more information, please visit Unity.

Unity is a proud equal opportunity employer. We are committed to fostering an inclusive, innovative environment and celebrate our employees across age, race, color, ancestry, national origin, religion, disability, sex, gender identity or expression, sexual orientation, or any other protected status in accordance with applicable law. Our differences are strengths that enable us to support the growing and evolving needs of our customers, partners, and collaborators. If you have a disability that means there are preparations or accommodations we can make to help ensure you have a comfortable and positive interview experience, please fill out this form to let us know.

Pursuant to the San Francisco Fair Chance Ordinance, we will consider for employment qualified applicants with arrest and conviction records.

This position requires the incumbent to have a sufficient knowledge of English to have professional verbal and written exchanges in this language since the performance of the duties related to this position requires frequent and regular communication with colleagues and partners located worldwide and whose common language is English.

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

Your privacy is important to us. Please take a moment to review our Prospect Privacy Policy and Applicant Privacy Policy. Should you have any concerns about your privacy, please contact us at DPO@unity.com.

#Sen #Li-Ar1

*Note: Certain locations require a good faith disclosure of the base salary range for the role. The actual salary for the successful candidate may differ based on location, experience, and other job-related factors.

\nGross pay salary$165,600—$248,400 USD","hiringOrganization":{"@type":"Organization","name":"Unity","sameAs":"https://unity.com/"},"jobLocation":{"@type":"Place","address":{"@type":"PostalAddress","addressLocality":"San Francisco, CA, USA","addressCountry":"United States","addressRegion":"North America"}}}},{"@type":"ListItem","position":40,"item":{"@type":"JobPosting","title":"Senior Machine Learning Engineer, Ads Foundation Modeling","datePosted":"2025-09-22","description":"

What you'll be doing

Design, implement, and maintain high-performance CTR and CVR prediction models that power ad ranking and recommendation systems.
Build and refine systems for creative understanding and user behavior modeling, enabling more accurate and context-aware engagement predictions.
Ensure model quality and reliability by continuously monitoring performance, calibrating predictions, and addressing data drift or delayed feedback.
Actively participate and work with other leads to set the long term direction for the team, plan and oversee engineering designs and project execution.
Effectively communicate complex technical concepts to non-engineering stakeholders.

What we're looking for

Advanced degree (MS or Ph.D.) in Computer Science, Machine Learning, Statistics, related field, or equivalent practical experience.
5+ years of hands-on experience building and operating large-scale Ads delivery and optimization systems.
3+ years of experience building CTR/CVR systems, content understanding, or behavior modeling systems.
Significant experience in one or more general-purpose programming languages like Python, Go, Scala, C++ or similar.
Knowledge of metric design, experimentation methodologies, and large-scale data analysis.

You might also have

Experience designing and productionizing optimization algorithms in an ad serving platform and/or other marketplaces.
Experience with state-of-the-art control systems, reinforcement learning algorithms.

Additional Information

International relocation support is not available for this position.
Life at Unity
We offer a wide range of benefits designed to support employees' well-being and work-life balance. You can read more about them on our career page.

\n\n

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

#Sen #Li-Ar1

\nGross pay salary$165,600—$248,400 USD","hiringOrganization":{"@type":"Organization","name":"Unity","sameAs":"https://unity.com/"},"jobLocation":{"@type":"Place","address":{"@type":"PostalAddress","addressLocality":"Remote, USA","addressCountry":"United States","addressRegion":"North America"}}}},{"@type":"ListItem","position":41,"item":{"@type":"JobPosting","title":"Senior Machine Learning Engineer, Ads Foundation Modeling","datePosted":"2025-09-22","description":"

What you'll be doing

Design, implement, and maintain high-performance CTR and CVR prediction models that power ad ranking and recommendation systems.
Build and refine systems for creative understanding and user behavior modeling, enabling more accurate and context-aware engagement predictions.
Ensure model quality and reliability by continuously monitoring performance, calibrating predictions, and addressing data drift or delayed feedback.
Actively participate and work with other leads to set the long term direction for the team, plan and oversee engineering designs and project execution.
Effectively communicate complex technical concepts to non-engineering stakeholders.

What we're looking for

Advanced degree (MS or Ph.D.) in Computer Science, Machine Learning, Statistics, related field, or equivalent practical experience.
5+ years of hands-on experience building and operating large-scale Ads delivery and optimization systems.
3+ years of experience building CTR/CVR systems, content understanding, or behavior modeling systems.
Significant experience in one or more general-purpose programming languages like Python, Go, Scala, C++ or similar.
Knowledge of metric design, experimentation methodologies, and large-scale data analysis.

You might also have

Experience designing and productionizing optimization algorithms in an ad serving platform and/or other marketplaces.
Experience with state-of-the-art control systems, reinforcement learning algorithms.

Additional Information

International relocation support is not available for this position.
Life at Unity
We offer a wide range of benefits designed to support employees' well-being and work-life balance. You can read more about them on our career page.

\n\n

Pursuant to the San Francisco Fair Chance Ordinance, we will consider for employment qualified applicants with arrest and conviction records.

#Sen #Li-Ar1

\nGross pay salary$165,600—$248,400 USD","hiringOrganization":{"@type":"Organization","name":"Unity","sameAs":"https://unity.com/"},"jobLocation":{"@type":"Place","address":{"@type":"PostalAddress","addressLocality":"San Francisco, CA, USA","addressCountry":"United States","addressRegion":"North America"}}}},{"@type":"ListItem","position":42,"item":{"@type":"JobPosting","title":"Senior Machine Learning Engineer, Ads Foundation Modeling","datePosted":"2025-09-22","description":"

What you'll be doing

Design, implement, and maintain high-performance CTR and CVR prediction models that power ad ranking and recommendation systems.
Build and refine systems for creative understanding and user behavior modeling, enabling more accurate and context-aware engagement predictions.
Ensure model quality and reliability by continuously monitoring performance, calibrating predictions, and addressing data drift or delayed feedback.
Actively participate and work with other leads to set the long term direction for the team, plan and oversee engineering designs and project execution.
Effectively communicate complex technical concepts to non-engineering stakeholders.

What we're looking for

Advanced degree (MS or Ph.D.) in Computer Science, Machine Learning, Statistics, related field, or equivalent practical experience.
5+ years of hands-on experience building and operating large-scale Ads delivery and optimization systems.
3+ years of experience building CTR/CVR systems, content understanding, or behavior modeling systems.
Significant experience in one or more general-purpose programming languages like Python, Go, Scala, C++ or similar.
Knowledge of metric design, experimentation methodologies, and large-scale data analysis.

You might also have

Experience designing and productionizing optimization algorithms in an ad serving platform and/or other marketplaces.
Experience with state-of-the-art control systems, reinforcement learning algorithms.

Additional Information

International relocation support is not available for this position.
Life at Unity
We offer a wide range of benefits designed to support employees' well-being and work-life balance. You can read more about them on our career page.

\n\n

Pursuant to the San Francisco Fair Chance Ordinance, we will consider for employment qualified applicants with arrest and conviction records.

#Sen #Li-Ar1

\nGross pay salary$165,600—$248,400 USD","hiringOrganization":{"@type":"Organization","name":"Unity","sameAs":"https://unity.com/"},"jobLocation":{"@type":"Place","address":{"@type":"PostalAddress","addressLocality":"Remote, USA","addressCountry":"United States","addressRegion":"North America"}}}},{"@type":"ListItem","position":43,"item":{"@type":"JobPosting","title":"Machine Learning Engineer","datePosted":"2025-09-22","description":"

Machine Learning Engineer

About Rent the Runway

Founded in 2009, Rent the Runway is disrupting the trillion-dollar fashion industry and changing the way women get dressed through the Closet in the Cloud, the world’s first and largest shared designer closet. RTR’s mission has remained the same since its founding: powering women to feel their best every day. Through RTR, customers can subscribe, rent items a-la-carte and shop resale from hundreds of designer brands. The Closet in the Cloud offers a wide assortment of millions of items for every occasion, from evening wear and accessories to ready-to-wear, workwear, denim, casual, maternity, outerwear, blouses, knitwear, loungewear, jewellery, handbags, activewear, ski wear, home goods and kidswear. RTR has built a two-sided discovery engine, which connects deeply engaged customers and differentiated brand partners on a powerful platform built around its brand, data, logistics and technology. Under CEO and Co-Founder Jennifer Hyman’s leadership, RTR has been named to CNBC’s “Disruptor 50” five times in ten years, and has been placed on Fast Company’s Most Innovative Companies list four times, while Hyman herself has been named to the “TIME 100: Most Influential People in the World\" and as one of People Magazine’s “Women Changing the World.”

Galway Office

Rent The Runway established its European Technology Hub in Galway in April 2019. Based in the historic Claddagh area of the city, the growing team in Galway tackles core technology challenges and influences the next generation of services critical to Rent The Runway’s success and continued growth.

The Galway office is Rent the Runway's first international office outside the US and enables the company to significantly expand its Software Engineering, Product Development, Machine Learning Engineering and Data Science footprint. Rent The Runway’s Galway-based employees have the opportunity to grow their careers across several roles and career paths in Technology.

Our engineering team is smart, pragmatic, and entrepreneurial. We practice continuous integration & test-driven development, engage in constant peer code reviews & pair programming, and work hard to give back to the software community through open-source contributions.

About The Role:

Machine Learning Engineers at Rent the Runway create data products that have tangible effects on our customer experience and internal operations. You will own projects end to end, from framing which problems to tackle through transforming information from our massive data ecosystem into actionable insights, and ultimately building & integrating algorithms into our network of services in collaboration with our product & software engineering teams.

You will have the opportunity to impact all parts of our business: determining what inventory assortment to buy, optimizing the lifespan of that inventory, establishing the right network of warehouses & transportation methods to best serve our customers, personalizing the user experience, optimizing user acquisition & retention, investigating how we can improve customer service by serving the right information at the right time, optimally pricing clothing rentals and sales, forecasting demand and more.

We are always interested in speaking with developing and experienced Machine Learning engineers interested in joining our team. If that’s you, read on for a snapshot of the type of work our Machine Learning engineers do across our various teams, share your details and a member of our Talent team will be in touch!

What You’Ll Do:

Work on a team of peers in an environment that will keep you constantly challenged and learning new things every day.
Develop and deploy performant algorithms powering customer-facing applications that are core to our business and success.
Collaborate closely in an equal partnership with our business, product and engineering teams.
Have a significant voice both in what you work on and how the work is carried out.

About You:

3+ years work experience building data products, preferably with Python, and integrating them into internal and customer-facing applications in production environments. Bonus points if you’ve: built & maintained services using AWS, GCP; deployed & maintained production deep learning models using frameworks such as Tensorflow, PyTorch, Keras in a business environment.
Ability and desire to own your project through its entire lifecycle, from data exploration and analysis to modelling, experimentation, production implementation, monitoring, and communication with stakeholders.
Experience transforming vague problems into algorithmic solutions
Desire to drive serious business impact and a bias to action. You like to move fast, you follow through, and you’re accountable to the results.
Owner’s mindset. No job is too big or too small, and you always leave things better than you found them.
An innate curiosity and an open mind.

Benefits:

At Rent the Runway, we’re committed to the happiness and wellbeing of our employees, and aim to create a workplace that fosters both personal and professional growth. Our inclusive benefits include, but are not limited to:

Generous Paid Time Off including annual leave, paid bereavement, and family sick leave - every employee needs time to take care of themselves and their family.
Universal Paid Parental Leave for both parents + flexible return to work program - because we know your newest family member(s) deserve your undivided attention.
Paid Sabbatical after 5 years of continuous service - unplug, recharge, and have some fun.
Competitive Stakeholder Pension - taking care of your future.
Comprehensive health, dental care and dependents care from day 1 of employment - Your health comes first and we’ve got you covered.
Company wide events and outings - our team spirit is no joke - we know how to have fun!
Hybrid Work - This is a hybrid role based in our Galway, Ireland office. Employees have to option to work remotely 2-3 days per week.

Rent the Runway is an equal opportunity employer. In accordance with applicable law, we prohibit discrimination against any applicant or employee on any legally-recognised basis, including, but not limited to: gender, marital status, family status, age disability, sexual orientation, race, religion, and membership of the Traveller community.

#Li-Em1

By submitting your application below, you agree that you have read and acknowledge Rent the Runway's Candidate Privacy Policy, found here.

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We are seeking a highly skilled Staff ML Engineer to drive state-of-the-art bidding optimization systems that enable efficient budget pacing, goal-aligned automated strategies, continual improvement through experimentation, and sustainable growth for Unity Ads.

What you'll be doing

Design, implement, and maintain high-performance CTR and CVR prediction models that power ad ranking and recommendation systems.
Build and refine systems for creative understanding and user behavior modeling, enabling more accurate and context-aware engagement predictions.
Ensure model quality and reliability by continuously monitoring performance, calibrating predictions, and addressing data drift or delayed feedback.
Actively participate and work with other leads to set the long term direction for the team, plan and oversee engineering designs and project execution.
Effectively communicate complex technical concepts to non-engineering stakeholders.

What we're looking for

Advanced degree (MS or Ph.D.) in Computer Science, Machine Learning, Statistics, related field, or equivalent practical experience.
7+ years of hands-on experience building and operating large-scale Ads delivery and optimization systems.
3+ years of experience building CTR/CVR systems, content understanding, or behavior modeling systems.
Significant experience in one or more general-purpose programming languages like Python, Go, Scala, C++ or similar.
Knowledge of metric design, experimentation methodologies, and large-scale data analysis.

You might also have

Experience designing and productionizing optimization algorithms in an ad serving platform and/or other marketplaces.
Experience with state-of-the-art control systems, reinforcement learning algorithms.

Additional Information

International relocation support is not available for this position.
Work visa/immigration sponsorship is not available for this position
Life at Unity
We offer a wide range of benefits designed to support employees' well-being and work-life balance. You can read more about them on our career page.

\n\n

Pursuant to the San Francisco Fair Chance Ordinance, we will consider for employment qualified applicants with arrest and conviction records.

#Sen #Li-Ar1

\nGross pay salary$192,600—$288,800 USD","hiringOrganization":{"@type":"Organization","name":"Unity","sameAs":"https://unity.com/"},"jobLocation":{"@type":"Place","address":{"@type":"PostalAddress","addressLocality":"San Francisco, CA, USA","addressCountry":"United States","addressRegion":"North America"}}}},{"@type":"ListItem","position":45,"item":{"@type":"JobPosting","title":"Staff Machine Learning Engineer, Ads Foundation Modeling","datePosted":"2025-09-22","description":"

What you'll be doing

Design, implement, and maintain high-performance CTR and CVR prediction models that power ad ranking and recommendation systems.
Build and refine systems for creative understanding and user behavior modeling, enabling more accurate and context-aware engagement predictions.
Ensure model quality and reliability by continuously monitoring performance, calibrating predictions, and addressing data drift or delayed feedback.
Actively participate and work with other leads to set the long term direction for the team, plan and oversee engineering designs and project execution.
Effectively communicate complex technical concepts to non-engineering stakeholders.

What we're looking for

Advanced degree (MS or Ph.D.) in Computer Science, Machine Learning, Statistics, related field, or equivalent practical experience.
7+ years of hands-on experience building and operating large-scale Ads delivery and optimization systems.
3+ years of experience building CTR/CVR systems, content understanding, or behavior modeling systems.
Significant experience in one or more general-purpose programming languages like Python, Go, Scala, C++ or similar.
Knowledge of metric design, experimentation methodologies, and large-scale data analysis.

You might also have

Experience designing and productionizing optimization algorithms in an ad serving platform and/or other marketplaces.
Experience with state-of-the-art control systems, reinforcement learning algorithms.

Additional Information

International relocation support is not available for this position.
Work visa/immigration sponsorship is not available for this position
Life at Unity
We offer a wide range of benefits designed to support employees' well-being and work-life balance. You can read more about them on our career page.

\n\n

Pursuant to the San Francisco Fair Chance Ordinance, we will consider for employment qualified applicants with arrest and conviction records.

#Sen #Li-Ar1

\nGross pay salary$192,600—$288,800 USD","hiringOrganization":{"@type":"Organization","name":"Unity","sameAs":"https://unity.com/"},"jobLocation":{"@type":"Place","address":{"@type":"PostalAddress","addressLocality":"Remote, USA","addressCountry":"United States","addressRegion":"North America"}}}},{"@type":"ListItem","position":46,"item":{"@type":"JobPosting","title":"Staff Machine Learning Engineer, Ads Foundation Modeling","datePosted":"2025-09-22","description":"

What you'll be doing

Design, implement, and maintain high-performance CTR and CVR prediction models that power ad ranking and recommendation systems.
Build and refine systems for creative understanding and user behavior modeling, enabling more accurate and context-aware engagement predictions.
Ensure model quality and reliability by continuously monitoring performance, calibrating predictions, and addressing data drift or delayed feedback.
Actively participate and work with other leads to set the long term direction for the team, plan and oversee engineering designs and project execution.
Effectively communicate complex technical concepts to non-engineering stakeholders.

What we're looking for

Advanced degree (MS or Ph.D.) in Computer Science, Machine Learning, Statistics, related field, or equivalent practical experience.
7+ years of hands-on experience building and operating large-scale Ads delivery and optimization systems.
3+ years of experience building CTR/CVR systems, content understanding, or behavior modeling systems.
Significant experience in one or more general-purpose programming languages like Python, Go, Scala, C++ or similar.
Knowledge of metric design, experimentation methodologies, and large-scale data analysis.

You might also have

Experience designing and productionizing optimization algorithms in an ad serving platform and/or other marketplaces.
Experience with state-of-the-art control systems, reinforcement learning algorithms.

Additional Information

International relocation support is not available for this position.
Work visa/immigration sponsorship is not available for this position
Life at Unity
We offer a wide range of benefits designed to support employees' well-being and work-life balance. You can read more about them on our career page.

\n\n

Pursuant to the San Francisco Fair Chance Ordinance, we will consider for employment qualified applicants with arrest and conviction records.

#Sen #Li-Ar1

\nGross pay salary$192,600—$288,800 USD","hiringOrganization":{"@type":"Organization","name":"Unity","sameAs":"https://unity.com/"},"jobLocation":{"@type":"Place","address":{"@type":"PostalAddress","addressLocality":"San Francisco, CA, USA","addressCountry":"United States","addressRegion":"North America"}}}},{"@type":"ListItem","position":47,"item":{"@type":"JobPosting","title":"Staff Machine Learning Engineer, Ads Foundation Modeling","datePosted":"2025-09-22","description":"

What you'll be doing

Design, implement, and maintain high-performance CTR and CVR prediction models that power ad ranking and recommendation systems.
Build and refine systems for creative understanding and user behavior modeling, enabling more accurate and context-aware engagement predictions.
Ensure model quality and reliability by continuously monitoring performance, calibrating predictions, and addressing data drift or delayed feedback.
Actively participate and work with other leads to set the long term direction for the team, plan and oversee engineering designs and project execution.
Effectively communicate complex technical concepts to non-engineering stakeholders.

What we're looking for

Advanced degree (MS or Ph.D.) in Computer Science, Machine Learning, Statistics, related field, or equivalent practical experience.
7+ years of hands-on experience building and operating large-scale Ads delivery and optimization systems.
3+ years of experience building CTR/CVR systems, content understanding, or behavior modeling systems.
Significant experience in one or more general-purpose programming languages like Python, Go, Scala, C++ or similar.
Knowledge of metric design, experimentation methodologies, and large-scale data analysis.

You might also have

Experience designing and productionizing optimization algorithms in an ad serving platform and/or other marketplaces.
Experience with state-of-the-art control systems, reinforcement learning algorithms.

Additional Information

International relocation support is not available for this position.
Work visa/immigration sponsorship is not available for this position
Life at Unity
We offer a wide range of benefits designed to support employees' well-being and work-life balance. You can read more about them on our career page.

\n\n

#Sen #Li-Ar1

\nGross pay salary$192,600—$288,800 USD","hiringOrganization":{"@type":"Organization","name":"Unity","sameAs":"https://unity.com/"},"jobLocation":{"@type":"Place","address":{"@type":"PostalAddress","addressLocality":"Remote, USA","addressCountry":"United States","addressRegion":"North America"}}}},{"@type":"ListItem","position":48,"item":{"@type":"JobPosting","title":"Machine Learning Engineer Intern, Agentic ML (Summer 2026)","datePosted":"2025-09-22","description":"

Join Us In Building The Future Of Finance.

Our mission is to democratize finance for all. An estimated $124 trillion of assets will be inherited by younger generations in the next two decades. The largest transfer of wealth in human history. If you’re ready to be at the epicenter of this historic cultural and financial shift, keep reading.

About The Team + Role

We are building an elite team, applying frontier technologies to the world’s biggest financial problems. We’re looking for bold thinkers. Sharp problem-solvers. Builders who are wired to make an impact. Robinhood isn’t a place for complacency, it’s where ambitious people do the best work of their careers. We’re a high-performing, fast-moving team with ethics at the center of everything we do. Expectations are high, and so are the rewards.

The Agentic team at Robinhood is building the foundation for AI agents that power the next generation of AI financial products and internal tools. Our mission is to empower teams across the company to rapidly build, evaluate, and deploy high-performance AI agents through intuitive tooling, production-grade infrastructure, and continuous optimization support. We’re creating a platform that makes it easy for engineers to experiment, ship, and scale agents reliably.

We’re looking for a passionate and curious Machine Learning Intern to join us in advancing this mission and learning alongside a world-class team of ML engineers.

What You’Ll Do

Build and prototype tools and workflows for agent development that support rapid prototyping—define agents, compose toolchains, and construct reasoning loops with minimal overhead.
Assist in building platform solutions to support scalable experimentation, synthetic dataset generation, and multi-agent evaluation across diverse tasks and domains.
Maintain feedback and optimization pipelines that incorporate both automated metrics and human-in-the-loop evaluation signals to fine-tune agent behavior.
Support fine-tuned models in production environments with robust evaluation, rollback strategies, and performance monitoring.
Collaborate closely with applied AI/ML teams to translate state-of-the-art research in agentic reasoning, planning, and tool use into reliable, production-ready systems.

What You Bring

Pursuing a degree in Computer Science, Data Science, Statistics, Engineering, or a related technical field, with an expected graduation date in Winter 2026 or Spring 2027.
Solid foundation in software engineering, machine learning principles, algorithms, and data structures.
Familiarity with Python and basic ML frameworks (e.g., scikit-learn, PyTorch, or TensorFlow).
Interest in building agentic systems and large language models.
A collaborative mindset and strong communication skills.

Base pay for the successful applicant will depend on a variety of job-related factors, which may include education, training, experience, location, business needs, or market demands. The expected hourly range for this role is based on the location where the work will be performed and is aligned to one of 3 compensation zones. For other locations not listed, compensation can be discussed with your recruiter during the interview process.

Zone 1 (Menlo Park, CA; New York, NY; Bellevue, WA; Washington, DC)$48—$48 USDZone 2 (Denver, CO; Westlake, TX; Chicago, IL)$42—$42 USDZone 3 (Lake Mary, FL; Clearwater, FL; Gainesville, FL)$37—$37 USD

Click here to learn more about our Total Rewards, which vary by region and entity.

If our mission energizes you and you’re ready to build the future of finance, we look forward to seeing your application.

Robinhood provides equal opportunity for all applicants, offers reasonable accommodations upon request, and complies with applicable equal employment and privacy laws. Inclusion is built into how we hire and work—welcoming different backgrounds, perspectives, and experiences so everyone can do their best. Please review the Privacy Policy for your country of application.

","hiringOrganization":{"@type":"Organization","name":"Robinhood","sameAs":"https://robinhood.com/"},"jobLocation":{"@type":"Place","address":{"@type":"PostalAddress","addressLocality":"Menlo Park, CA","addressCountry":"United States","addressRegion":"North America"}}}},{"@type":"ListItem","position":49,"item":{"@type":"JobPosting","title":"Machine Learning Engineer Intern, Applied ML (Summer 2026)","datePosted":"2025-09-22","description":"

Join Us In Building The Future Of Finance.

About The Team + Role

The mission of the Applied Machine Learning team is to develop scalable, data- and model-driven solutions that enhance decision-making across Robinhood. We focus on personalizing user experiences, helping customers discover and engage with the most valuable products and features. To empower ML adoption company-wide, we’re also building accessible model development tools that democratize machine learning at Robinhood.

We’re looking for a passionate and curious Machine Learning Intern to join us in advancing this mission and learning alongside a world-class team of ML engineers.

What You’Ll Do

Build and Prototype ML Models: Work on early-stage ranking, recommendation, and personalization models using techniques like collaborative filtering, content-based filtering, or learning-to-rank approaches.
Experimentation & Evaluation: Assist in setting up and analyzing A/B tests and offline experiments to evaluate the effectiveness of ML algorithms.
Explore and Analyze Data: Dive into rich datasets to extract signals and support data-driven feature engineering and model tuning.
Collaborate Cross-Functionally: Work with engineers, data scientists, and product managers to understand business needs and help integrate ML into real product use cases.
Contribute to Internal Tools: Help improve model development tools, document findings, and support reusable libraries that enable broader adoption of ML practices.

What You Bring

Pursuing a degree in Computer Science, Data Science, Statistics, Engineering, or a related technical field, with an expected graduation date in Winter 2026 or Spring 2027.
Solid foundation in machine learning principles, algorithms, and data structures.
Familiarity with Python and basic ML frameworks (e.g., scikit-learn, PyTorch, or TensorFlow).
Interest in recommendation systems, personalization, or reinforcement learning.
Enthusiasm for working with large datasets and running experiments to learn what works.
A collaborative mindset and strong communication skills.

Click here to learn more about our Total Rewards, which vary by region and entity.

If our mission energizes you and you’re ready to build the future of finance, we look forward to seeing your application.

","hiringOrganization":{"@type":"Organization","name":"Robinhood","sameAs":"https://robinhood.com/"},"jobLocation":{"@type":"Place","address":{"@type":"PostalAddress","addressLocality":"Menlo Park, CA","addressCountry":"United States","addressRegion":"North America"}}}},{"@type":"ListItem","position":50,"item":{"@type":"JobPosting","title":"Senior Machine Learning Engineer - Databricks (m/f/*)","datePosted":"2025-09-22","description":"

Our Engineering community is growing, and we’re now looking for a Senior ML Engineer - Databricks (m/f/*) to join our team in Nepal, supporting our global growth.

\n\n\n

As a Senior Machine Learning Engineer (m/f/*), you will lead the design and implementation of advanced data and AI solutions on the Databricks Lakehouse Platform. Your focus will lie in building robust ML pipelines, enabling GenAI capabilities, and delivering production-grade solutions that support data-driven innovation at scale.

\n\n\n\n\n\n

What We Offer

\n\n\n

A chance to accelerate your career and work with outstanding colleagues in a supportive learning community split across 3 continents
Contribute your ideas to our unique projects and make an impact by turning them into reality
Balance your work and personal life through our workflow organization and decide yourself if you work at home, in the office, or on a hybrid setup
Annual performance review, and regular feedback cycles, generating distinct value by connecting colleagues through networks rather than hierarchies
Individual development plan, professional development opportunities
Educational resources such as paid certifications, unlimited access to Udemy Business, etc.
Local, virtual, and global team events, in which UT colleagues become acquainted with one another

\n\n\n

What You’Ll Do

\n\n

Design, develop, and maintain scalable machine learning pipelines on the Databricks Lakehouse Platform using Spark, Delta Lake, and MLflow.
Perform exploratory data analysis (EDA), data cleaning, feature engineering, and model evaluation to support data-driven use cases.
Collaborate with data engineers and business stakeholders to translate real-world problems into ML solutions.
Deploy models using MLflow, manage model versioning, and set up monitoring and retraining strategies.
Optimize the performance and cost-efficiency of ML workloads on Databricks clusters.
Apply best practices in MLOps, ensuring reproducibility, governance, and scalability of ML solutions.
Guide and mentor team members on Databricks, ML engineering best practices

\n\n\n\n\n\n

What You’Ll Bring

\n\n\n

Hands-on experience with Databricks (on Azure, AWS, or GCP), especially Spark (PySpark or Scala), Delta Lake, and MLflow.
Deep understanding of the machine learning lifecycle, including data prep, modeling, evaluation, and deployment.
Proficiency in Python, with solid foundations in ML libraries (e.g., scikit-learn, pandas).
Experience building production-ready ML pipelines and working with large-scale datasets.
Familiarity with orchestration tools (e.g., Databricks Workflows, Airflow) and version control (Git/GitHub).
Strong problem-solving and communication skills, with the ability to explain complex models and logic to stakeholders.
Fluent English communication skills (written and spoken).

Nice To Have

Experience with MLOps workflows: model monitoring, automated retraining, A/B testing.
Exposure to cloud-native architectures, CI/CD for ML, and infrastructure-as-code (e.g., Terraform).
Knowledge of Databricks Unity Catalog for model governance and security.
Experience working in regulated or enterprise data environments.

\n\n\n

Did we pique your interest, or do you have any questions?

\n\n\n

We want to hear from you: contact us at recruit@ultratendency.com

\n\n\n \n\n

About Us

\n\n\n

Ultra Tendency is an international premier Data Engineering consultancy for Big Data, Cloud, Streaming, IIoT and Microservices. We design, build, and operate large-scale data-driven applications for major enterprises such as the European Central Bank, HUK-Coburg, Deutsche Telekom, and Europe’s largest car manufacturer. Founded in Germany in 2010, UT has developed a reliable client base and now runs 8 branches in 7 countries across 3 continents.

\n\n\n

We do more than just leverage tech, we build it. At Ultra Tendency we contribute source code to +20 open-source projects including Ansible, Terraform, NiFi, and Kafka. Our impact on tech and business is there for anyone to see. Enterprises seek out Ultra Tendency because we solve the problems others cannot.

\n\n\n

We love the challenge: together, we tackle diverse and unique projects you will find nowhere else. In our knowledge community, you will be a part of a supportive network, not a hierarchy. Constant learning and feedback are our drivers for stable development. With us you can develop your individual career through work-life balance.

\n\n\n\n

We evaluate your application based on your skills and corresponding business requirements. Ultra Tendency welcomes applications from qualified candidates regardless of race, ethnicity, national or social origin, disability, sex, sexual orientation, or age.

\n\n\n

Data privacy statement: Data Protection for Applicants – Ultra Tendency

","hiringOrganization":{"@type":"Organization","name":"Ultra Tendency","sameAs":"https://www.ultratendency.com/"},"jobLocation":{"@type":"Place","address":{"@type":"PostalAddress","addressLocality":"Kathmandu, Bagmati, Nepal","addressCountry":"Nepal","addressRegion":"Asia/Pacific"}}}}]}

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