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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":2,"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.

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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":3,"item":{"@type":"JobPosting","title":"Senior Machine Learning Engineer","datePosted":"2025-09-22","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.

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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

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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.

\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.

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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":"Quito","addressCountry":"Ecuador","addressRegion":"South America"}}}},{"@type":"ListItem","position":4,"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":"Lima","addressCountry":"Peru","addressRegion":"South America"}}}},{"@type":"ListItem","position":5,"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":6,"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.

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 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.

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":"Remote, USA","addressCountry":"United States","addressRegion":"North America"}}}},{"@type":"ListItem","position":7,"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.

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.

#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":8,"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":9,"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":10,"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

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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.

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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.

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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.

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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.

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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"}}}},{"@type":"ListItem","position":11,"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 Germany, supporting our global growth.

\n\n\n

\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 German & 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

\n\n\n\n

\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":"Magdeburg, Saxony-Anhalt, Germany","addressCountry":"Germany","addressRegion":"Europe"}}}},{"@type":"ListItem","position":12,"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, to join our team in Spain, supporting our global growth.

\n\n\n

As a Senior Machine Learning Engineer, 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

\n\n\n\n

\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":"Madrid, Madrid, Spain","addressCountry":"Spain","addressRegion":"Europe"}}}},{"@type":"ListItem","position":13,"item":{"@type":"JobPosting","title":"Senior Machine Learning Engineer (Fulfilment)","datePosted":"2025-09-22","description":"

Company Description

About Grab and Our Workplace

Grab is Southeast Asia's leading superapp. From getting your favourite meals delivered to helping you manage your finances and getting around town hassle-free, we've got your back with everything. In Grab, purpose gives us joy and habits build excellence, while harnessing the power of Technology and AI to deliver the mission of driving Southeast Asia forward by economically empowering everyone, with heart, hunger, honour, and humility.

Job Description

Get to Know the Team

The Fulfilment Tech Family is a foundational part of Grab, enabling seamless coordination between our diverse marketplaces across Southeast Asia. We design real-time, distributed systems and machine learning solutions to process hundreds of millions of requests per day, driving efficient supply allocation, pricing, and order matching. Our mission:

Deliver best-in-class products for our driver-partners.
Maximise efficiency in fulfilling consumer demand – rain or shine.
Create sustainable, efficient marketplaces that balance experience and cost for all stakeholders.

We're looking for a Senior Machine Learning Engineer to join our Fulfilment team and take the lead in Fulfilment strategy optimization – bringing existing optimisation and automation of our pricing, dispatch and supply management policies to the next level.

Get to Know the Role

You'll optimize cross-system fulfilment strategies, and lead model development with user and driver behavioural prediction, optimisation and reinforcement learning (RL) techniques. Your primary objective will be to enhance marketplace operations by constructing interpretable, adaptable multi-agent RL systems or decision agents that can manage diverse objectives and disruptions.

You'll report to the Head of Data Science and work onsite at Grab's One North Singapore office.

The Critical Tasks You Will Perform

You'll design and implement cross-system strategies to improve operational efficiency in fulfilling user demands and boosting driving utilisation.
You'll build advanced DL and LLM models to capture the spatial-temporal patterns of dynamic marketplace conditions.
You'll develop advanced ML/DL models to predict user and driver behaviours, and use the behavioural insights to inform decision-making and platform interventions.
You'll build and deploy interpretable, adaptable optimisation models, RL systems or decision agents, that can handle multi-objectives and real-world disruptions.
You'll collaborate with machine learning engineers and backend engineers to integrate the ML/DL, optimization or RL models into real-time production systems.
You'll create technical documents outlining the methodologies and findings of your work. You'll also present solutions to non-technical stakeholders.

Qualifications

What Essential Skills You Will Need

You hold a Master degree in Computer Science, Operations Research, Applied Mathematics, or related field with at least 2 years of relevant experience.
You have professional experience or academic publications in Reinforcement Learning, Stochastic Control, Behavioural Modelling, Optimisation Under Uncertainty.
You have experience developing and deploying ML models that incorporate online learning, Markov Decision Processes, or simulation-based optimization.
You are fluent in Python and ML frameworks (e.g., PyTorch, TensorFlow).
You are familiar with distributed computing systems or scalable training platforms (e.g., Spark, Ray).
You can explore new ideas and learn new skills to accomplish tasks.

Additional Information

Life At Grab

We care about your well-being at Grab, here are some of the global benefits we offer:

We have your back with Term Life Insurance and comprehensive Medical Insurance.
With GrabFlex, create a benefits package that suits your needs and aspirations.
Celebrate moments that matter in life with loved ones through Parental and Birthday leave, and give back to your communities through Love-all-Serve-all (LASA) volunteering leave
We have a confidential Grabber Assistance Programme to guide and uplift you and your loved ones through life's challenges.
Balancing personal commitments and life's demands are made easier with our FlexWork arrangements such as differentiated hours

What We Stand For at Grab

We are committed to building an inclusive and equitable workplace that enables diverse Grabbers to grow and perform at their best. As an equal opportunity employer, we consider all candidates fairly and equally regardless of nationality, ethnicity, religion, age, gender identity, sexual orientation, family commitments, physical and mental impairments or disabilities, and other attributes that make them unique.

","hiringOrganization":{"@type":"Organization","name":"Grab","sameAs":"https://www.grab.com"},"jobLocation":{"@type":"Place","address":{"@type":"PostalAddress","addressLocality":"Singapore, Singapore","addressCountry":"Singapore","addressRegion":"Asia/Pacific"}}}},{"@type":"ListItem","position":14,"item":{"@type":"JobPosting","title":"Senior Machine Learning Engineer","datePosted":"2025-09-21","description":"

Weave is looking for engineers hungry for fun challenges who can join our self-empowered teams and contribute in both technical and non-technical ways.

You will be joining a team of talented developers that share a common interest in distributed backend systems, data, scalability, and continued development. You will get a chance to apply these, and other skills, to new and ongoing projects to make machine learning more approachable, data more available, and easier to discover and use by helping design how teams build out AI powered features at Weave.

Our teams are cross-functional agile teams composed of a product owner, backend and frontend devs and devops. Teams are highly autonomous with the ownership and ability to act in Weave’s best interest.

Above all, your work will impact the way our customers experience Weave while working closely with a highly skilled team to accomplish varying goals and cultivate our phenomenal culture.

Purpose

The Machine Learning Team's mission is to enable product innovation by making it painless for developers to build ai powered applications that require access to large sets of data. Machine learning is challenging but we are striving to democratize access to the tools and technology that powers it so teams can build cutting edge features safely and responsibly without a PhD in Data Science. As a Machine Learning Engineer on the team you’ll be building models for new products with emerging technologies, at scale. We handle data for hundreds of millions of people daily.

This position will be available for fully remote in the US with an opportunity to work in an office, if located near the Lehi, UT Headquarters.
Reports to: Engineering Director

What You Will Own

Design and Develop machine learning infrastructure, tooling, and models to help teams deliver world class experiences.
Help product and development teams understand the data lifecycle and the inherent experimental nature of machine learning.
Build internal products and platforms to enable teams to incorporate AI into their features and customer facing products.
Consult with teams to help them understand common patterns, anti-patterns, and tradeoffs of machine learning. Guide them through creating excellent customer experiences end to end.
Build scalable, resilient services to support data integration, event processing, and platform extensions.
Contribute to the continued evolution of product functionality that services large amounts of data and traffic.
Write code that is high-quality, performant, sustainable, and testable while holding yourself accountable for the quality of the code you produce.
Coach and collaborate inside and outside the team. You enjoy working closely with others - helping them grow by sharing expertise and encouraging best practices.
Work in a cloud environment, considering the implementation of functionality through several distributed components and services.
Work with our stakeholders to translate product goals into actionable engineering plans.

What You Will Need to Accomplish the Job

High integrity, team-focused approach, and collaboration skills to build tight-knit relationships across Weave with various roles and stakeholders.
Responsive person with a strong bias for action.
5+ years of experience in any structured back-end language, i.e. Go, Java or Python (Go and Python experience is a plus).
Experience moving and storing TBs of data or 100M’s to 10B’s of records.
Experience building and deploying ML driven B2B multi-tenant applications in production environments.
Experience with common ML technologies such as Python, Jupyter, Workflow Engines (Dagster, MLFlow, KubeFlow, etc), DVC, Triton Server, LLMs, Postgres, and others.
Experience with modern ML tools and techniques such as LLMs, RAG, Prompt Engineering, Fine Tuning, multi-modal models, and others.
Experience with data labelling or annotation for audio or text use cases.
Understanding of distributed systems and building scalable, redundant, and observable services.
Expertise in designing and architecting systems for distributed data sets and services.
Experience building solutions to run on one or more of the public clouds (e.g., AWS, GCP, etc.).
Experience providing stable well designed libraries and SDKs for internal use.
Self driven and a thirst for learning in a quickly changing industry.
Demonstrated track record of delivering complex projects on time and have experience working in enterprise-grade production environments.
Strategic thinker with a strong technical aptitude and a passion for execution.

What Will Make Us Love You

A background with data analysis, visualization, and presentation.
3+ years of experience in data science, machine learning, or predictive analytics in addition to engineering experience.
Experience with natural language models, embeddings, and inference in production, at scale.
Experience with real-time audio models and voice use cases such as transcription, ASR pipelines with interruption detection, audio alignment, and speech synthesis.
Experience with emerging technologies such as Model Context Protocol (MCP).
Proficient understanding of containers, orchestrators, and usage patterns at scale including networking, storage, service meshes, and multi-cluster communication. Experience with Kubernetes or GKE and the Operator Pattern (GCP), specifically, a plus.
Experience with highly sensitive data such as PHI (HIPAA) and PII data.
Experience with automation and container based workflow engines.
Experience with GitOps, IaC, and configuration driven systems.
A preference for open source solutions.
A track record of clean abstractions and simple to use APIs.
Deep understanding of distributed data technologies such as streaming, data mesh, data lakes, warehouses, or distributed machine learning.
A desire to advance the state of the art with new and innovative technologies.
Enjoys working in a greenfield environment using rapid prototyping.
Enjoys working with open-ended, evolving problems, and domains.

Weave is an equal opportunity employer that is committed to fostering an inclusive workplace where all individuals are valued and supported. We welcome anyone who is hungry to learn, problem-solve and progress regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability, gender identity, veteran status, or other applicable legally protected characteristics. If you have a disability or special need that requires accommodation, please let us know.

All official correspondence will occur through Weave branded email. We will never ask you to share bank account information, cash a check from us, or purchase software or equipment as part of your interview or hiring process.

","hiringOrganization":{"@type":"Organization","name":"Weave","sameAs":"https://www.getweave.com/"},"jobLocation":{"@type":"Place","address":{"@type":"PostalAddress","addressLocality":"US Remote","addressCountry":"United States","addressRegion":"North America"}}}},{"@type":"ListItem","position":15,"item":{"@type":"JobPosting","title":"Senior Machine Learning Engineer (5+ years) | Nepal","datePosted":"2025-09-21","description":"About Docsumo:Docsumo is your go-to Document AI solution for streamlining business operations. We turn complex documents like bank statements, policies, and financial statements into valuable, actionable data. Our cutting-edge technology helps businesses make smarter decisions faster. We are backed by marquee investors such as Sequoia, Barclays, Fifth Wall, Common Ocean, and Techstars.
At Docsumo, we're on a mission to revolutionize how businesses handle data. We empower companies to:Boost efficiency by 6-10 timesMake quick, accurate decisions from unstructured informationScale operations effortlessly through innovative technology\n

The Opportunity As Senior Machine Learning Engineer:

We are seeking senior professionals with over 4 years of experience in the field. This is a role for candidates with a proven track record in machine learning, deep learning, NLP, and computer vision.
If you have led and managed a team of ML scientists and engineers and have a strong foundation in deploying end-to-end ML solutions, this opportunity is for you.
This role offers the chance to rapidly advance into leadership positions, such as Lead ML Engineer, where you'll spearhead critical projects with creative autonomy.
You'll work closely with our CTO, Data Science, and Engineering teams, shaping the future of intelligent document processing for our expanding client base in the US.
This is a full-time role with flexible options, including hybrid work in Kathmandu or remote work from India.
Working hours are 10:00 am to 7:00 pm IST, with a 1-hour lunch break.
You will report directly to the Data Science Lead or the CTO, collaborating with a talented team to deliver innovative ML solutions that drive customer success.

Key Responsibilities

Collaborate with cross-functional teams of scientists and engineers to design, develop, and implement advanced machine learning systems that transform innovative ideas from conceptual stages into operational APIs.
Conduct cutting-edge research in machine learning, focusing on the application and fine-tuning of Large Language Models (LLMs) to develop robust, scalable solutions for intelligent document processing.
Lead a team of data scientists and machine learning engineers, providing mentorship and fostering a culture of collaboration and continuous learning to achieve high performance and innovative outcomes.
Plan, manage, and oversee the full lifecycle of ML projects, ensuring alignment with business goals and timely delivery of high-quality solutions. Develop and apply sophisticated machine learning algorithms to address complex business challenges, particularly those involving the processing and analysis of unstructured data.
Engage in Agile development processes including regular standups, sprint planning, and retrospectives to facilitate iterative progress and maintain high standards of output.
Ensure the documentation of machine learning methodologies, model development processes, and maintain rigorous testing standards to ensure reliability and efficiency of models in production.
Drive the integration and optimization of LLMs and other advanced models to enhance performance and operational efficiency, continuously seeking improvements.

Need To Have:

At least 5 years of industry experience in machine learning, deep learning, NLP, and computer vision, ideally within tech companies, product startups, or R&D environments.
1-2 years of experience leading teams of 4-5+ ML scientists and engineers, demonstrating effective leadership and project management skills. Proficiency in PyTorch and TensorFlow, with experience in training deep neural networks, implementing transfer learning, and optimizing models.
Strong skills in classification and regression techniques, with hands-on experience in Scikit-learn, Numpy, Pandas, and Scipy. Practical experience with Transformers, such as BERT and GPT, for tasks like text classification, entity recognition, and sentiment analysis.
Proficiency in Python and strong understanding of Object-Oriented Programming (OOP) principles.
Experience with version control using Git, cloud platforms like AWS and Google Cloud, and containerization technologies such as Docker and Kubernetes.
Ability to work effectively in a team, demonstrating motivation, resourcefulness, and a growth mindset.
Bachelor’s degree in Computer Science, Statistics, Machine Learning, Physics, Mathematics, or a related field.

Nice To Have:

Experience with Large Language Models, including techniques like PEFT, prompt engineering, few-shot learning, and RLHF.
Knowledge of computer vision applications like OCR, OpenCV, CNNs, and multimodal AI.
Experience with advanced data visualization libraries.
Familiarity with Agile development practices and sprint management.
A track record of innovative research contributions or publications in the machine learning domain.

","hiringOrganization":{"@type":"Organization","name":"Docsumo","sameAs":"https://www.docsumo.com/"},"jobLocation":{"@type":"Place","address":{"@type":"PostalAddress","addressLocality":"Kathmandu, Nepal","addressCountry":"Nepal","addressRegion":"Asia/Pacific"}}}},{"@type":"ListItem","position":16,"item":{"@type":"JobPosting","title":"Senior Machine Learning Engineer","datePosted":"2025-09-20","description":"

At Prodigal, we’re reshaping the future of consumer finance. Founded in 2018 by IITB alumni, our journey began with one bold mission: to eradicate the inefficiencies and confusion that have plagued the lending and collections industry for decades.

Today, we stand at the forefront of a seismic shift in the industry, pioneering the concept of consumer finance intelligence. Powered by our cutting-edge platform, Prodigal’s Intelligence Engine, we’re creating the next-generation agentic workforce for consumer finance—one that empowers companies to achieve unprecedented levels of operational excellence.

With over half a billion consumer finance interactions processed and a growing impact on more than 100 leading companies across North America, we’ve established ourselves as the go-to partner for organizations that demand more from their AI solutions. Our unparalleled experience, coupled with our trusted customer relationships, uniquely positions us to build generative AI solutions that will revolutionize the future of consumer finance.

At Prodigal, we are driven by a singular, unrelenting purpose: to transform how consumer finance companies engage with their customers and, in turn, drive successful outcomes for all.

We are looking for a passionate and seasoned Senior Machine Learning (ML) Engineer to spearhead the design, development, and deployment of cutting-edge Machine Learning and Generative AI solutions towards Prodigal’s vision of building the Intelligence Layer for Consumer Finance.

Responsibilities:

ML Algorithm Development: Design and implement advanced ML algorithms leveraging traditional Machine Learning techniques and the modern NLP stack, including Large Language Models (LLMs)
Data Engineering & Software Development: Architect and implement data pipelines for ML model training. Lead scalable software systems development to deploy ML models into production systems, ensuring high performance and reliability.
Research & Innovation: Stay updated on ML research and the ever-changing Gen AI landscape, identifying opportunities for innovation.
Collaboration & Leadership: Effectively collaborate with cross-functional teams to deliver high-quality solutions on time. Guide team members in contributing to ML design discussions for new projects.

Requirements:

Extensive experience (5-8 years) in software development, with a focus on machine learning and data science in a tech company.
Proven track record of delivering high-quality ML products in a fast-paced, agile environment.
Deep understanding of machine learning algorithms with hands-on experience in developing and deploying machine learning models at scale.
Strong coding skills in Python. Familiarity with machine learning libraries such as PyTorch and sci-kit-learn. Experience with data manipulation and analysis tools like Pandas and Spark.
Strong communication and leadership skills, with the ability to effectively collaborate with cross-functional teams and mentor junior engineers.

Preferred Qualifications:

Experience training and using Large Language Models (BERT, LLAMA, GPT etc) with a passion for applying Generative AI solutions in production environments.
Experience with cloud services (AWS) and building scalable, distributed systems.

Mode Of Work - In-Office

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Job Benefits

World-class team - You'll get the chance to learn from (and teach) some of the brightest and most skilled people you'll ever meet. Our team members have been part of BCG, Deloitte, EY, Blackstone, Meta, Amazon and are IIT, IIM, BITS alumnus.
Continuous education - As relentless seekers of knowledge, we sponsor and support any training materials, books, courses, and exam fees for upskilling yourself in areas related to your role - but that's not where it ends. If you make a good case for some extra learning, we're delighted to foot the tab.
Food at the office – Meals are on us. We won't let your stomach grumble while you hustle.
Health insurance - Health always comes first. The health of your family is as important to us, as it is to you. We offer insurance coverage for both you and your family.
Flexible schedule - We're not a \"clock in, clock out\" company. Morning person? Start work while the world's still sleeping. Night owl? Ramp things up while others are winding down. You're fully trusted to create the right conditions for your own personal peak productivity. We only ask that you be available to your teammates for seamless collaboration.
Generous leave policy - Take all the time you need to recharge your batteries - no cap on vacation allowance here. Because a rested, relaxed, and refreshed mind is a happy and effective mind.
Recreation & team activities – We regularly indulge in friendly football, table tennis, cooking sessions and challenge each other to do those extra push ups or chug that 4th drink (of course that’s Nimbu Pani)

\n\n

Meet Sangram - (Cofounder and CTO) and hear his vision for Prodigal below (01:38)

From day 1, Prodigal has been defined by talented, humble, and hungry leaders and we want this mindset and culture to continue to blossom from top to bottom in the company. If you have an entrepreneurial spirit and want to work in a fast-paced, intellectually-stimulating environment where you will be pushed to grow, then please reach out because we are looking to build a transformational company that reinvents one of the biggest industries in the US.

To learn more about us - please visit the following:
Our Story - https://www.prodigaltech.com/our-story
What shapes our thinking - https://link.prodigaltech.com/our-thesis
Our website - https://www.prodigaltech.com/

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About Definitive Healthcare:

At Definitive Healthcare (NASDAQ: DH), we’re passionate about turning data, analytics, and expertise into meaningful intelligence that helps our customers achieve success and shape the future of healthcare. We empower them to uncover the right markets, opportunities, and people—paving the way for smarter decisions and greater impact.

We’re headquartered in Framingham, Massachusetts, but we have 3 office locations globally, including locations in Sweden, and India. We’ve grown significantly since our founding in 2011 and have expanded our global client base to 2,400+.

We’re also a great place to work. In 2024, we brought home a number of awards including Built In’s 100 Best Places to Work in Boston, a Stevie Bronze Award for Great Employers, and we were recognized as a Great Place to Work in India.

We foster a collaborative, inclusive culture where diverse perspectives drive innovation. Through programs like DefinitiveCares and our employee-led affinity groups we strive to promote connection, education, and inclusion.

We are looking for a Senior Machine Learning Engineer to lead the design and implementation of cutting-edge AI/ML systems that deliver transformative business outcomes. In this role, you will take ownership of end-to-end ML solutions, from architecture and modeling to production and performance optimization.

From architecting end-to-end ML solutions to shaping technical strategy, your work will have a broad and lasting impact on customer experience and operational efficiency. The ideal candidate brings extensive experience in applied machine learning, deep software engineering expertise, and a track record of mentoring teams and delivering production-ready models at scale. This is a high-impact, full-stack ML role that blends research, engineering, and leadership, with the opportunity to shape both the company’s technical foundation and product direction.

Responsibilities:

ML Systems Development & Deployment

Lead the design and implementation of scalable, production-grade ML systems in cloud environments with a focus on performance, reliability, and reproducibility.
Collaborate with product managers and senior stakeholders to define and prioritize ML initiatives aligned with business goals.

Data Pipeline & Feature Engineering

Oversee the architecture and evolution of data pipelines for multi-terabyte datasets, ensuring efficiency and reliability.
Guide the development of high-impact features and label sets across diverse domains such as healthcare and consumer analytics

Experimentation & Model Management

Lead experimentation strategy, including design of A/B tests, advanced validation methods, and lifecycle management using tools like MLflow and Databricks.
Drive continual model improvement through advanced techniques such as automated retraining, model decay analysis, and bias mitigation. Innovation & Prototyping
Champion rapid prototyping and proof-of-concept development to evaluate emerging technologies and ML techniques.
Lead technical explorations into new ML architectures (e.g., foundation models, causal inference, time series deep learning).

Cross-Functional Collaboration

Serve as a technical leader and trusted advisor, working closely with product, engineering, data, and executive teams to shape end-to-end ML solutions. Code Quality & Documentation
Set standards for code quality, performance, and documentation, and mentor junior engineers in best practices

Required Qualifications:

Bachelor’s or Master’s degree in Computer Science, Machine Learning, Data Science, or a related field (or equivalent practical experience).
5+ years of industry experience as an ML Engineer, Data Scientist, or Data Engineer, with a focus on deploying and scaling ML systems.
Deep expertise in Python, SQL, and PySpark for distributed data processing, with proficiency in libraries like scikit-learn, PyTorch, and XGBoost.
Proven experience designing robust ML pipelines, leveraging tools like MLflow or equivalent.
Strong command of ML frameworks (e.g., scikit-learn, TensorFlow, XGBoost, PyTorch).
Hands-on experience deploying models in cloud-based environments (AWS, GCP, Azure, and Databricks).
Proven ability to manage end-to-end ML lifecycles at scale, including data ingestion, training, evaluation, deployment, and monitoring.
Excellent communication skills and demonstrated ability to influence cross-functional teams.

Preferred Qualifications:

Experience working with healthcare claims, EHR, or life sciences datasets.
Advanced degree (M.S. or Ph.D.) in Computer Science, Data Science, or related technical field.
Strong knowledge of MLOps practices including CI/CD for ML, automated retraining, and model versioning.
Experience with deep learning architectures for time series forecasting, sequential data, or hierarchical modeling.
Proficient in designing evaluation protocols and defining performance metrics to rigorously assess model effectiveness and drive data-driven decision-making.
Comfortable operating in fast-paced, high-ownership environments, and able to prioritize multiple high-impact projects

Why we love Definitive, and why you will too!

Industry leading products
Work hard, and have fun doing it
Incredibly fast growth means limitless opportunity
Flexible and dynamic culture
Work alongside some of the most talented and dedicated teammates
Definitive Cares, our community service group, gives all of us a chance to give back
Competitive benefits package including great healthcare benefits and a 401(k) match

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What our Employees are saying about us on Glassdoor:

“Great Work atmosphere, great work life balance, excellent company to work for, amazing top notch product, incredible customer service, lots of tools to help you succeed.”

-Business Development Manager

“Great team. Amazing growth. Employees are treated very well.”

-Research Analyst

“I have waited 36 years to work at a dream job for a dream company and I am so happy to have finally got there.”

-Profile Analyst

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If you don’t fit all of these qualifications, but believe you’re still a great fit, feel free to apply and tell us why in your cover letter.

If you are a California, Colorado, New York City or Washington resident and this role is a remote role, you can receive additional information about the compensation and benefits for this role, which we will provide upon request.

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Definitive Hiring Philosophy

Definitive Healthcare is an equal opportunity employer that celebrates diversity and is committed to creating an inclusive workplace with equal opportunity for all applicants and teammates. Our goal is to recruit the most talented people from a diverse candidate pool regardless of race, color, religion, age, gender, gender identity, sexual orientation or any other status. If you’re interested in working in a fast growing, exciting working environment – we encourage you to apply!

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Privacy
Your privacy is important to us. Please review our Candidate Privacy Notice which tells you how we use and process your personal information.

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Please note: All communications regarding the hiring process at Definitive Healthcare will come directly from one of our corporate recruiters or coordinators with an @definitivehc.com email address. We will never request any money transfer or purchase of equipment with a promise of reimbursement. If you receive any suspicious communications, please reach out to careers@definfitivehc.com to confirm your status in the application process.

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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

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About Us

TakeUp, LLC is revolutionizing revenue optimization for hospitality with a daring approach to pricing. Using AI and machine learning, TakeUp empowers independent operators to unlock maximum revenue potential through pricing courageously—day in, day out. Seamlessly integrated with top Property Management Systems, our platform replaces traditional rate-setting constraints with data-driven confidence, delivering an impressive 10-15x ROI.

The Opportunity

We are hiring a Senior Machine Learning Engineer to focus on applied modeling for our rate optimization engine. This role is hands-on: designing, training, and deploying models that turn hotel data into reliable production outcomes. You will collaborate closely with the ML Engineering Manager, the CTO, and product partners to design modeling approaches, build pipelines, and support experiments that drive measurable revenue impact.

What You’Ll Do

Modeling

Design, train, and deploy production ML models, with emphasis on tree-based methods (XGBoost, LightGBM, CatBoost).
Contribute to feature engineering and model evaluation approaches that balance accuracy, interpretability, and speed.
Translate customer needs and product requirements into practical modeling tasks (classification, regression, ranking, uplift).
Develop custom performance metrics to evaluate models’ ability to generate reasonable counterfactual demand estimates while accounting for varying customer product expectations.
Support explainability efforts to justify rate decisions with clear artifacts and documentation.

Pipelines & Deployment

Build and maintain training and evaluation pipelines, ensuring offline metrics align with online business outcomes.
Partner with engineering to integrate models into production services and batch jobs with defined SLAs.
Contribute production ready Python and SQL code with strong testing and review practices.
Support data quality, observability, and reproducibility across the ML lifecycle.

Experimentation

Collaborate on experiment design, including A/B testing and staged rollouts.
Implement policy guardrails to ensure automated rate changes are safe and controlled.
Analyze experimental results, communicate lift and trade-offs, and document findings.

Collaboration

Work closely with product, engineering, and leadership to scope problems and propose modeling approaches.
Participate in code reviews, model reviews, and planning sessions.
Share learnings and contribute to improving team practices around modeling, metrics, and documentation.

Who You Are

4+ years of experience building and deploying ML models to production.
Proficiency in Python (scikit-learn, XGBoost/LightGBM/CatBoost).
Strong SQL skills and comfort with large, imperfect, real-world datasets.
Experience across the full model lifecycle: data preparation, feature engineering, training, evaluation, deployment, and monitoring.
Familiarity with experimentation design and metrics; able to reason about trade-offs and safeguards.
Clear communicator, comfortable working in a collaborative, fast-paced environment.

Nice To Have

Experience with causal inference (uplift modeling, causal forests, DML) or time-series modeling.
Exposure to reinforcement learning concepts (multi-armed bandits, dynamic programming, temporal-difference learning).
Experience with cloud data warehouses (Snowflake, BigQuery, Redshift) and dbt.
Familiarity with orchestration frameworks (Prefect, Airflow).
Familiarity with MLOps frameworks (Sagemaker, Vertex AI)
Domain knowledge in pricing, demand modeling, or hospitality.
Former start-up experience.

Why Takeup?

At TakeUp, we empower our team to innovate, grow, and succeed. You’ll join a passionate group of professionals who are committed to changing the way businesses run. This is mission-driven work: we’re empowering independent inns and small hotels, businesses often underserved and outgunned by enterprise competitors, with technology that levels the playing field.

Ready to take your career to the next level with a fast-growing SaaS company? Apply now and let's make an impact together!

Travel

This role is remote. While flexibility is key, we also value in-person connections. Travel may be needed for customer discovery, team building, and/or networking.

EQUAL OPPORTUNITY EMPLOYER
1848 Ventures celebrates diversity and is committed to inclusion. All qualified applicants receive consideration for employment without regard to race, color, sex, religion, national origin, age, sexual orientation, gender identity, disability, or status as a protected veteran.

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Company Description

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

Job Description

The Opportunity:

We are looking for a versatile, curious, and energetic Senior Machine Learning Engineer to join our team of passionate and dedicated engineers. We are the backbone for Data Engineering and Machine Learning developments at Visa and we thrive on solving complex challenges on a global scale! As a Senior Machine Learning Engineer, you will be an integral part of a multi-functional development team inventing, designing, building, and testing products that reach a truly global customer base.

You will face big challenges and question the status quo, changing the way data products are developed at Visa! Come join us and see your efforts shape the digital future of payments.

The Work Itself:

The Senior ML Engineer, as a part of our Generative AI team, will play a multifaceted role in the design, development, and deployment of our Large Language Model (LLM) applications. Key responsibilities will include creating applications based on the Retrieval-Augmented Generation (RAG) framework, developing efficient inferencing algorithms, and fine-tuning the LLM to cater to various applications.

This role will also involve leveraging various machine learning stacks to enhance system efficiency, researching new techniques to advance our LLM applications, and collaborating with cross-functional teams within the organization. In addition, the engineer will be responsible for documenting processes and workflows and sharing insights with the team.

This position requires a solid understanding of AI and machine learning principles, robust problem-solving skills, and the ability to thrive in a fast-paced, dynamic environment.

Essential Functions:

Collaborate with project team members (Product Managers, Architects, Analysts, Software Engineers, Project Managers, etc.) to ensure development and implementation of new data driven business solutions.
Drive development effort End-to-End for on-time delivery of high quality solutions that conform to requirements, conform to the architectural vision, and comply with all applicable standards. Responsibilities span all phases of solution development including:
Collaborate with senior technical staff and PM to identify, document, plan contingency, track and manage risks and issues until all are resolved
Present technical solutions, capabilities, considerations, and features in business terms. Effectively communicate status, issues, and risks in a precise and timely manner.

This is a hybrid position. Expectation of days in office will be confirmed by your Hiring Manager.

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, or PhD)
Preferred Qualifications:
•3 or more years of work experience with a Bachelor’s Degree or more than 2 years of work experience with an Advanced Degree (e.g. Masters, MBA, JD, MD)
•Exposure to leading-edge areas such as Machine Learning, Big Data, Distributed Systems or SRE.
•Experience in at least one of the following: Python, Golang, Java, or C/C++
•Familiarity with web service standards and related patterns (REST, gRPC)
•Experience implementing solutions for low-latency, distributed services using open standard technologies.

Additional Information

Work Hours: Varies upon the needs of the department.

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

U.S. APPLICANTS ONLY: The estimated salary range for a new hire into this position is $130,700.00 to $184,440.00 to 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.

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Company Description

We are Nifty Coders Pvt. Ltd., a leading provider of Enterprise-Grade Software Engineering Services for startups and corporates. As experts in DevOps & Infrastructure, Application Development, and Service Reliability Engineering (SRE), we deliver innovative, reliable, and scalable solutions that drive business success and digital transformation.

Our commitment to excellence and industry best practices enables us to build high-quality, secure, and tailored software solutions that empower businesses to thrive. With a proven track record of successfully executing complex cloud migration and deployment automation projects, we are dedicated to helping our clients navigate the ever-evolving digital landscape, fostering long-term partnerships and growth.

Job Description

We are looking for a Senior ML Engineer to drive the development and deployment of scalable machine learning solutions. In this role, you will design, train, and optimize advanced models, build robust data pipelines, and collaborate with engineering and product teams to integrate AI capabilities into our systems. As a senior member of the team, you will establish best practices, mentor junior engineers, and lead initiatives that enhance automation, model reliability, and overall performance to deliver impactful, data-driven solutions.

Responsibilities:

Study, analyze, and transform business requirements into data science prototypes.
Design and implement machine learning systems using traditional ML algorithms (e.g., tree-based models, clustering), recommendation systems and transformer –based architectures.
Build, fine-tune, and deploy Large Language Models (LLMs), including local open-source LLMs (e.g., LLaMA, Mistral, Qwen) and API-based models.
Develop Generative AI applications, including Retrieval-Augmented Generation (RAG) pipelines using vector databases (e.g., FAISS, ChromaDB, Milvus).
Run machine learning tests and experiments.
Train and retrain algorithms when necessary.
Extend existing ML libraries and frameworks.
Keep abreast of developments in the field.

Qualifications

Years of Experience: Minimum 5+ years of professional experience in software development, specializing in ML.
Education: Bachelor’s or Master’s degree in Computer Science, Data Science, or a related field.

Requirements:

Proven experience as a Machine Learning Engineer or similar role
Understanding of data structures, data modeling and software architecture
Ability to write robust code in Python.
Hands-on experience with transformers and Hugging Face ecosystem.
Hands-on experience with Agentic frameworks like LangChain/LangGraph.
Familiarity with machine learning frameworks (like Keras or PyTorch) and libraries (like scikit-learn)

Additional Information

Employment Type: Full-time
Weekend: 2 Days
Work Model: Hybrid

Compensation And Benefits:

Join a Workplace That Values You

At Nifty Coders Pvt. Ltd., we celebrate innovation, collaboration, and the unique contributions each of our employees brings. We prioritize a work environment that encourages growth, well-being, and a healthy work-life balance. Here, you’ll be part of a team that values creativity, promotes flexibility, and empowers individuals to thrive.

As part of our commitment to supporting you, we offer a range of benefits and perks designed to enhance your work experience:

Competitive compensation plans
Two annual bonuses
Paid Maternity Leave (4 months) and Paternity Leave (5 working days)
Comprehensive medical insurance for you and your dependents
Monthly and quarterly team-building events
Transport allowance
Mobile and internet allowance
Subsidized daily lunch
A dynamic performance review process that fosters ongoing transparency between managers and team members
Company-sponsored certifications programs for internal career growth and development

At Nifty Coders, we foster a culture of collaboration, continuous learning, and innovation, ensuring that every employee has the opportunity to grow and succeed.

Application Deadline: October 15, 2025

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WHY JOIN US?

To work with a team of dynamic ML engineers and R&D team in a fast-growing start-up.
Contribute to KLAARA’s product development roadmap.
Identify and train suitable machine learning models to be used in conjunction with trading algorithms for complex problems.
Oversee the full ML model training lifecycle from data preprocessing to model serving.
Design and implement ML pipelines to allow for proper tracking of data trained models Deliver POC.
Progress within the state-of-the-art AI environment.
Fine-tune the current model and implement it.
Understand, analyse and define new models to create new use cases.
Lead a team of engineers.

Requirements

Ph.D or Master's Degree in Computer Science, Artificial Intelligence, Data Science is preferred.
Experience in ML model training/fine-tuning from Data preprocessing all the way to model serving.
Experience in optimising performance of ML models Experience with ML pipe lining tools.
Full proficiency in Python, R.
Understanding of basic Git commands.
Proficiency in Linux-based operating systems.
Strong knowledge in Machine Learning and Deep Learning (CNN, RNN, Random Forest, SVM, etc).
Experience with Document AI understanding, and extraction is a big plus.
Experience with Pytorch or Tensorflow.
Knowledge of DevOps CI/CD tools such as Jenkins.
Knowledge of container tools such as Docker and Kubernetes Github repository with projects is a big plus (we want to see what you have been able to create).
Ability to solve technical challenges and solutions.
Good command of spoken & written English and Mandarin.
A fast learner and able to work independently.

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Company Description

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

Job Description

Team Overview:

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

What you get to do in this role:

Design, develop, and evaluate end-to-end machine learning solutions, with a focus on large language models (LLMs), combining engineering rigor and research depth.
Lead the development of PoCs and applied research prototypes to explore novel AI capabilities, model interpretability, and safety strategies.
Conduct cutting-edge experiments to assess model behaviour, generalization, and fairness across diverse datasets and use cases.
Generate and curate synthetic and real-world datasets to optimize model robustness, reliability, and performance.
Fine-tune and deploy large-scale models, incorporating prompt engineering, few-shot learning, and retrieval-augmented techniques.
Collaborate cross-functionally with product, research, and engineering teams to publish white papers, participate in conferences, and contribute to open-source or peer-reviewed ML/AI research.
Define and implement rigorous evaluation protocols, including human-in-the-loop testing, bias detection, and safety metrics.
Develop CI/CD pipelines and containerized workflows for scalable training, evaluation, and deployment of ML solutions in production.
Identify risks in AI applications and contribute to responsible AI initiatives, including transparency, robustness, and compliance frameworks.

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
5+ years of experience in machine learning, deep learning, or data science, with a track record of applied research or experimentation.
Strong proficiency in Python and ML frameworks such as PyTorch, TensorFlow, HuggingFace Transformers, and NumPy.
Hands-on experience with prompt engineering, model training, evaluation, and optimization for LLMs or foundation models.
Proven experience in applied research, academic publication, technical blogging, or contributions to open-source ML projects.
Familiarity with data-centric AI workflows: synthetic data generation, labelling strategies, and dataset versioning tools.
Deep understanding of AI/ML evaluation strategies, model robustness techniques, and responsible AI practices.
Practical experience deploying models using inference platforms like Triton, ONNX in production environments.
Experience working with MLOps stacks: CI/CD, experiment tracking (e.g., MLflow), Docker, Kubernetes, and distributed training frameworks.
Excellent communication skills with the ability to explain complex ML ideas to non-technical stakeholders and contribute to scientific documentation.

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":24,"item":{"@type":"JobPosting","title":"Senior Machine Learning Engineer","datePosted":"2025-09-19","description":"Cherre is the real estate industry's leading data management platform, powering more than $3 trillion AUM globally. Our end-to-end platform helps clients connect, transform, analyze, and act on trusted data to increase efficiencies, reduce risks, gain visibility into market trends, and make strategic moves in response to changing market conditions.
We are looking to add a Machine Learning Engineer to our team. This role will be responsible for developing products that provide ML-powered insights to our customers and integrating those applications into the Cherre tech pipeline. Candidates must have an R&D / research background as well as industry-based engineering experience deploying models into production.
The work we do at Cherre touches multiple aspects of ML - the ideal candidate should be familiar with such diverse topics as deep learning, graph algorithms, and named entity resolution. Ability to implement algorithms at scale and experience with distributed computing / big data applications is critical - our knowledge graph has billions of edges!\n

Responsibilities

Work within an agile fullstack scrum team to deploy ML models into production
Develop new ML-based services that enhance our data capabilities
Design and implement scalable and repeatable ML pipelines
Collaborate with data engineering to design workflows for ingesting data streams required for ML applications

Requirements

2+ years software experience, preferably in an object-oriented language
3+ year experience deploying ML models in a production environment Industry-based experience with big data / distributed computing applications
Familiarity with current NLP technologies
Languages: Python, SQL
Technologies: Airflow, Kubernetes, Docker, GCP stack

Nice To Haves

Masters degree in Computer Science / Engineering discipline
Publications / patents in the field of machine learning
Technologies: Apache Spark

Starting Goals

30 Day
Familiar with the Cherre tech stack
Exposure to the Cherre release process
Understands company and team goals
Assigned a mini-project that they will own
60 Day
Familiar with the existing Cherre ML pipeline
Able to start contributing PRs
Understands the types of data we ingest and common customer use cases
90 Day
Contributing to the ML pipeline on a daily basis
Mini-project is completed

Benefits

Competitive Base Salary
Equity
Range of Healthcare Plans
Paid Parental Leave
Unlimited Vacation
Flexible Work Schedule
Compensation: $155,000-220,000/ year

If this opportunity sounds interesting, apply or reach out to our internal talent team. We are happy to tell you more about Cherre: the technology we work with, the problems we solve, the team we are assembling, and the culture we all contribute to. We are excited you are considering working with us and look forward to hearing from you!
“At the top of the mountain we are all snow leopards.” - Hunter S. Thompson
Cherre is an equal opportunity employer. We pride ourselves on hiring the best people for the job no matter their race, sex, orientation, nationality, religion, disability, or age.","hiringOrganization":{"@type":"Organization","name":"Cherre","sameAs":"https://cherre.com/"},"jobLocation":{"@type":"Place","address":{"@type":"PostalAddress","addressLocality":"New York, New York","addressCountry":"United States","addressRegion":"North America"}}}},{"@type":"ListItem","position":25,"item":{"@type":"JobPosting","title":"Senior Machine Learning Engineer – AI Agent Platform","datePosted":"2025-09-19","description":"

At GEICO, we offer a rewarding career where your ambitions are met with endless possibilities.

Every day we honor our iconic brand by offering quality coverage to millions of customers and being there when they need us most. We thrive through relentless innovation to exceed our customers’ expectations while making a real impact for our company through our shared purpose.

When you join our company, we want you to feel valued, supported and proud to work here. That’s why we offer The GEICO Pledge: Great Company, Great Culture, Great Rewards and Great Careers.

Position Description

GEICO is seeking an experienced Sr ML engineer to join our AI org. This person will play key roles for the development of Geico’s virtual assistant platform that elevates the productivity for 30K+ internal associates and the customer experience for millions of policyholders. You will be collaborating with a dynamic team of AI and software engineers to design, develop and deploy systems that ensure productivity, scalability and usability of GenAI workflows across Geico. AI Agent Platform Engineers are responsible for building key multi-tenant services that power the building, testing, simulation, deployment and hosting of LLM-based agents. The ideal candidate should demonstrate a proven track record of building high performance AI/ML platform & systems, with hands-on experience and deep enthusiasm for Generative AI and related ecosystems.

Responsibilities:

Own design, development and maintenance of high-performance, durable and scalable platform components that jointly power large sets of end-to-end GenAI agentic workflows. Examples include AI agent building & deployment, prompt management, workflow orchestration, MCP registry, etc.
Contribute to the selection, evaluation, and implementation of software platforms, tools, and frameworks, balancing build vs. buy, speed to market, maintainability, etc.
Collaborate with cross-functional teams, including data scientists, ML engineers, software engineers, product managers, designers to gather requirements, define project scope and prioritize feature backlogs. Establish pragmatic technical visions & roadmaps that balance business outcome, product release timelines and engineering excellence.
Assist in the planning and estimation of software development projects, ensuring the efficient allocation of resources and timely delivery of solutions.
Mentor and guide junior engineers via code reviews and design sessions, fostering a collaborative and high-performance team culture, elevating AI engineering best practices across the company.

Basic Qualifications

5+ years of professional software development experience with at least two general-purpose programming languages such as Java, C++, Python or C#.
4+ years of experience designing and building AIML platform and systems utilizing open-source/cloud-agnostic components such as search engine (e.g. elastic search, Qdrant), data warehouse (e.g. snowflake), streaming platform (e.g. Kafka), relational database (e.g. postgresql), Nosql (e.g. MongoDB, Cassandra), distributed processing (e.g. Spark, Ray), workflow management (e.g. Airflow, Temporal), memory management (e.g. Redis), etc.
3+ years’ experience managing end-to-end software development life cycle (version control, CICD pipelines, Kubernetes clusters, testing, monitoring & alerting, production support etc.)
3+ years’ experience building training, finetuning, real-time/batch inferencing and evaluation systems for AIML models and LLMs, esp. utilizing GPU-powered infrastructure
Bachelor’s degree or above in Computer Science, Engineering, Statistics or a related field

Preferred Qualifications:

3+ years’ experience with cloud providers such as Azure and AWS
2+ years’ experience building conversational experiences and agentic workflows, leveraging open source LLMs, e.g. Llama, Mistral, Claude etc.
Experience with LLM observability software such as Langsmith, Arize Phoenix, etc.
Experience building LLM-based AI agent workflows via both no code/low code and traditional high-code development environments
Strong communication and problem-solving skills to excel in dynamic, cross-functional decision-making environments

Annual Salary

$115,000.00 - $230,000.00

The above annual salary range is a general guideline. Multiple factors are taken into consideration to arrive at the final hourly rate/ annual salary to be offered to the selected candidate. Factors include, but are not limited to, the scope and responsibilities of the role, the selected candidate’s work experience, education and training, the work location as well as market and business considerations.

GEICO will consider sponsoring a new qualified applicant for employment authorization for this position.

The Geico Pledge:

Great Company: At GEICO, we help our customers through life’s twists and turns. Our mission is to protect people when they need it most and we’re constantly evolving to stay ahead of their needs.

We’re an iconic brand that thrives on innovation, exceeding our customers’ expectations and enabling our collective success. From day one, you’ll take on exciting challenges that help you grow and collaborate with dynamic teams who want to make a positive impact on people’s lives.

Great Careers: We offer a career where you can learn, grow, and thrive through personalized development programs, created with your career – and your potential – in mind. You’ll have access to industry leading training, certification assistance, career mentorship and coaching with supportive leaders at all levels.

Great Culture: We foster an inclusive culture of shared success, rooted in integrity, a bias for action and a winning mindset. Grounded by our core values, we have an an established culture of caring, inclusion, and belonging, that values different perspectives. Our teams are led by dynamic, multi-faceted teams led by supportive leaders, driven by performance excellence and unified under a shared purpose.

As part of our culture, we also offer employee engagement and recognition programs that reward the positive impact our work makes on the lives of our customers.

Great Rewards: We offer compensation and benefits built to enhance your physical well-being, mental and emotional health and financial future.

Comprehensive Total Rewards program that offers personalized coverage tailor-made for you and your family’s overall well-being.
Financial benefits including market-competitive compensation; a 401K savings plan vested from day one that offers a 6% match; performance and recognition-based incentives; and tuition assistance.
Access to additional benefits like mental healthcare as well as fertility and adoption assistance.
Supports flexibility- We provide workplace flexibility as well as our GEICO Flex program, which offers the ability to work from anywhere in the US for up to four weeks per year.

The equal employment opportunity policy of the GEICO Companies provides for a fair and equal employment opportunity for all associates and job applicants regardless of race, color, religious creed, national origin, ancestry, age, gender, pregnancy, sexual orientation, gender identity, marital status, familial status, disability or genetic information, in compliance with applicable federal, state and local law. GEICO hires and promotes individuals solely on the basis of their qualifications for the job to be filled.

GEICO reasonably accommodates qualified individuals with disabilities to enable them to receive equal employment opportunity and/or perform the essential functions of the job, unless the accommodation would impose an undue hardship to the Company. This applies to all applicants and associates. GEICO also provides a work environment in which each associate is able to be productive and work to the best of their ability. We do not condone or tolerate an atmosphere of intimidation or harassment. We expect and require the cooperation of all associates in maintaining an atmosphere free from discrimination and harassment with mutual respect by and for all associates and applicants.

","hiringOrganization":{"@type":"Organization","name":"GEICO","sameAs":"https://www.geico.com/"},"jobLocation":{"@type":"Place","address":{"@type":"PostalAddress","addressLocality":"MD Chevy Chase (Office) - JPS, United States","addressCountry":"United States","addressRegion":"North America"}}}},{"@type":"ListItem","position":26,"item":{"@type":"JobPosting","title":"Senior Machine Learning Engineer – AI Agent Platform","datePosted":"2025-09-19","description":"

At GEICO, we offer a rewarding career where your ambitions are met with endless possibilities.

When you join our company, we want you to feel valued, supported and proud to work here. That’s why we offer The GEICO Pledge: Great Company, Great Culture, Great Rewards and Great Careers.

Position Description

Responsibilities:

Own design, development and maintenance of high-performance, durable and scalable platform components that jointly power large sets of end-to-end GenAI agentic workflows. Examples include AI agent building & deployment, prompt management, workflow orchestration, MCP registry, etc.
Contribute to the selection, evaluation, and implementation of software platforms, tools, and frameworks, balancing build vs. buy, speed to market, maintainability, etc.
Collaborate with cross-functional teams, including data scientists, ML engineers, software engineers, product managers, designers to gather requirements, define project scope and prioritize feature backlogs. Establish pragmatic technical visions & roadmaps that balance business outcome, product release timelines and engineering excellence.
Assist in the planning and estimation of software development projects, ensuring the efficient allocation of resources and timely delivery of solutions.
Mentor and guide junior engineers via code reviews and design sessions, fostering a collaborative and high-performance team culture, elevating AI engineering best practices across the company.

Basic Qualifications

5+ years of professional software development experience with at least two general-purpose programming languages such as Java, C++, Python or C#.
4+ years of experience designing and building AIML platform and systems utilizing open-source/cloud-agnostic components such as search engine (e.g. elastic search, Qdrant), data warehouse (e.g. snowflake), streaming platform (e.g. Kafka), relational database (e.g. postgresql), Nosql (e.g. MongoDB, Cassandra), distributed processing (e.g. Spark, Ray), workflow management (e.g. Airflow, Temporal), memory management (e.g. Redis), etc.
3+ years’ experience managing end-to-end software development life cycle (version control, CICD pipelines, Kubernetes clusters, testing, monitoring & alerting, production support etc.)
3+ years’ experience building training, finetuning, real-time/batch inferencing and evaluation systems for AIML models and LLMs, esp. utilizing GPU-powered infrastructure
Bachelor’s degree or above in Computer Science, Engineering, Statistics or a related field

Preferred Qualifications:

3+ years’ experience with cloud providers such as Azure and AWS
2+ years’ experience building conversational experiences and agentic workflows, leveraging open source LLMs, e.g. Llama, Mistral, Claude etc.
Experience with LLM observability software such as Langsmith, Arize Phoenix, etc.
Experience building LLM-based AI agent workflows via both no code/low code and traditional high-code development environments
Strong communication and problem-solving skills to excel in dynamic, cross-functional decision-making environments

Annual Salary

$115,000.00 - $230,000.00

GEICO will consider sponsoring a new qualified applicant for employment authorization for this position.

The Geico Pledge:

As part of our culture, we also offer employee engagement and recognition programs that reward the positive impact our work makes on the lives of our customers.

Great Rewards: We offer compensation and benefits built to enhance your physical well-being, mental and emotional health and financial future.

Comprehensive Total Rewards program that offers personalized coverage tailor-made for you and your family’s overall well-being.
Financial benefits including market-competitive compensation; a 401K savings plan vested from day one that offers a 6% match; performance and recognition-based incentives; and tuition assistance.
Access to additional benefits like mental healthcare as well as fertility and adoption assistance.
Supports flexibility- We provide workplace flexibility as well as our GEICO Flex program, which offers the ability to work from anywhere in the US for up to four weeks per year.

","hiringOrganization":{"@type":"Organization","name":"GEICO","sameAs":"https://www.geico.com/"},"jobLocation":{"@type":"Place","address":{"@type":"PostalAddress","addressLocality":"CA Palo Alto - JPS, United States","addressCountry":"United States","addressRegion":"North America"}}}},{"@type":"ListItem","position":27,"item":{"@type":"JobPosting","title":"Senior Machine Learning Engineer, Domains Search","datePosted":"2025-09-18","description":"

The Domains Search team at Squarespace is building the next generation of intelligent search experiences for helping customers find the perfect domain. From applying large language models to produce creative domain suggestions, to building scalable ranking and personalization systems, our team is at the intersection of applied machine learning, natural language processing, and large-scale search infrastructure.

We are looking for a Senior Machine Learning Engineer to help shape and build this platform from the ground up. You will report to an Engineering Team Lead in our New York City headquarters.

Why Join Us

This is a unique opportunity to shape a greenfield ML initiative at Squarespace. You'll be part of a small, high-impact team building the foundation of how millions of customers discover and secure their online identity.

You'Ll Get To...

Design, build, and deploy ML models for domain search, including ranking, personalization, and generative domain name creation. Integrate and fine-tune LLMs and hybrid systems (LLMs + rule-based + classical ML) to create brandable, contextual, and internationalized domain suggestions.
Develop and evaluate ranking algorithms that optimize for multiple signals such as relevance, uniqueness, brandability, and business goals.
Implement personalization approaches leveraging user, account, and demographic data to tailor search results.
Collaborate with engineers, data scientists, and product managers to translate ambiguous product ideas into technical requirements and scalable ML solutions.
Own end-to-end ML lifecycle: from feature engineering, model training, and evaluation to deployment, monitoring, and iterative improvement.
Contribute to experimentation frameworks (A/B testing, Statsig, etc.) to measure model impact and continuously improve user experience.
Ensure search quality at scale by developing robust evaluation pipelines and metrics.

Who We'Re Looking For

5+ years of professional experience in machine learning engineering, with at least 2 years at a senior/lead IC level.
Strong background in search, ranking systems, or recommendation engines.
Experience with NLP and LLMs (prompt engineering, fine-tuning, or integration into production systems).
Proficiency in Python, ML frameworks (TensorFlow, PyTorch), and data tooling (Spark, SQL).
Experience deploying ML models to production and scaling them to handle large traffic volumes.
Familiarity with A/B testing and online experimentation methodologies.

Benefits & Perks

A choice between medical plans with an option for 100% covered premiums
Fertility and adoption benefits
Access to supplemental insurance plans for additional coverage
Headspace mindfulness app subscription
Global Employee Assistance Program
Retirement benefits with employer match
Flexible paid time off
20 weeks for parental leave and up to 12 weeks to care for an ill family member
Pretax commuter benefit
Education reimbursement
Employee donation match to community organizations
8 Global Employee Resource Groups (ERGs)
Dog-friendly workplace
Free lunch and snacks
Private rooftop
Hack week twice per year

Cash Compensation Range: $128,500 - $231,500 Usd

The base salary for this position will vary based on job-related criteria including relevant skills, experience, and location, among other factors.

In addition to the cash compensation above (which includes base salary and, where applicable for eligible roles, may include on-target commissions or overtime pay), Squarespace employees are eligible to be granted an option to purchase our common stock.

About Squarespace

Squarespace is a design-driven platform helping entrepreneurs build brands and businesses online. We empower millions of customers in more than 200 countries and territories with all the tools they need to create an online presence, build an audience, monetize, and scale their business. Our suite of products range from websites, domains, ecommerce, and marketing tools, as well as tools for scheduling with Acuity and creating and managing social media presence with Bio Sites and Unfold. Our team of more than 1,500 is headquartered in bustling New York City, with offices in Dublin, Ireland, Aveiro, Portugal, and coworking spaces in the UK, Netherlands, and Australia. For more information about our company culture, visit https://www.squarespace.com/about/careers.

Our Commitment

Today, more than a million people around the globe use Squarespace to share different perspectives and experiences with the world. Not only do we embrace and celebrate the diversity of our customers, but we also work toward the same in our employees. At Squarespace, we are committed to equal employment opportunity regardless of race, color, ethnicity, ancestry, religion, national origin, gender, sex, gender identity or expression, sexual orientation, age, citizenship, marital or parental status, disability, veteran status, or other class protected by applicable law. We are proud to be an equal opportunity workplace.

#Li-Hybrid

Thank you in advance for providing the following details about your work history from your resume! This helps us ensure that your candidate information is accurate and consistent during the hiring process.

\n\n

Squarespace will never solicit your personal banking information or ask you to transfer money in connection with a job offer or interview. We also will not reach out to you via phone or SMS without your permission or knowledge.

","hiringOrganization":{"@type":"Organization","name":"Squarespace","sameAs":"https://www.squarespace.com/"},"jobLocation":{"@type":"Place","address":{"@type":"PostalAddress","addressLocality":"New York City","addressCountry":"United States","addressRegion":"North America"}}}},{"@type":"ListItem","position":28,"item":{"@type":"JobPosting","title":"Senior Machine Learning Engineer, Simulation Realism","datePosted":"2025-09-18","description":"

Waymo is an autonomous driving technology company with the mission to be the world's most trusted driver. Since its start as the Google Self-Driving Car Project in 2009, Waymo has focused on building the Waymo Driver—The World's Most Experienced Driver™—to improve access to mobility while saving thousands of lives now lost to traffic crashes. The Waymo Driver powers Waymo’s fully autonomous ride-hail service and can also be applied to a range of vehicle platforms and product use cases. The Waymo Driver has provided over ten million rider-only trips, enabled by its experience autonomously driving over 100 million miles on public roads and tens of billions in simulation across 15+ U.S. states.

The Simulator Team at Waymo builds simulations of realistic environments for testing and training the Waymo Driver. We develop industry-leading simulation solutions using advanced ML algorithms that measure and enhance the performance of the Waymo Driver. By applying machine learning, we model the real world, including realistic agents (vehicles, pedestrians, cyclists, motorcyclists), roads, traffic control systems, and weather conditions.

To increase the fidelity and steerability of our simulations, we employ the latest ML technologies such as large foundation models trained on our datasets and diffusion technology. We also invest in capable infrastructure that allows us to quickly set up and roll out multiple scenarios to rigorously test our autonomous driving systems.

In this hybrid role, you will report to a Senior Staff Tech Lead Manager

You Will:

Drive innovation in ultra-realistic world simulation for autonomous vehicles. You will develop the latest simulation technologies using foundation models for embodied agents.
Apply your deep Machine Learning (ML) expertise, in Generative AI (GenAI), to push the boundaries of simulation realism and directly influence the advancement of autonomous driving technology.
Work with Waymo's foundational AI research team to transfer research into scalable and production-ready solutions.

You Have:

5+ years of experience with ML software engineering
5+ years of experience with Python
5+ years of ML software experience with machine learning framework including Pytorch, Tensorflow, Jax/Flax ,

We Prefer:

5+ years of experience creating and developing ML models
5+ years of experience with C++ in production setting, with experience integrating ML models in production system
5+ years of experience training large-scale models on GPU/TPU clusters are

#Li-Hybrid

The expected base salary range for this full-time position across US locations is listed below. Actual starting pay will be based on job-related factors, including exact work location, experience, relevant training and education, and skill level. Your recruiter can share more about the specific salary range for the role location or, if the role can be performed remote, the specific salary range for your preferred location, during the hiring process.

Waymo employees are also eligible to participate in Waymo’s discretionary annual bonus program, equity incentive plan, and generous Company benefits program, subject to eligibility requirements.

Salary Range$204,000—$259,000 USD","hiringOrganization":{"@type":"Organization","name":"Waymo","sameAs":"https://waymo.com/"},"jobLocation":{"@type":"Place","address":{"@type":"PostalAddress","addressLocality":"Mountain View, CA, USA","addressCountry":"United States","addressRegion":"North America"}}}},{"@type":"ListItem","position":29,"item":{"@type":"JobPosting","title":"Senior Machine Learning Engineer","datePosted":"2025-09-18","description":"

At Too Good To Go, we have an ambitious goal: to inspire and empower everyone to fight food waste together.

40% of all food produced in the world is wasted. And that has a huge impact on the health of our planet, with 10% of greenhouse gas emissions coming from food waste.

We’re more than an app: we are a certified B Corporation with a mission to empower everyone to take action against food waste, so alongside our marketplace app, we create educational tools, explore new business solutions - such as our Retail Technologies offering, and influence legislation to help reduce food waste.

We’re growing fast: Our community of 127 million registered users and 253,000 active partners across 20 countries, have together already prevented 489+ million meals from going to waste - avoiding over 1.322.000 tonnes of CO2e!

About The Role:

We're looking for a Senior Machine Learning Engineer to be a part of our Consumer Growth Product and Tech team that defines, builds, and delivers AI features for our marketing personalization efforts. You will work towards specific outcomes with the freedom and responsibility to figure out the best route to achieve them, collaborating with other engineers, data scientists, and product members. Within the Product & Tech organization, you will work toward generating the smartest possible recommendations for our users. Your work will ensure they are matched with the best meals at the right time, which in turn will result in more meals saved and improved user retention.

Your Mission

As a Senior Machine Learning Engineer, you will be part of a team dedicated to delivering a step-change in personalization for our consumer marketplace. You will of course collaborate with your counterparts in other product teams, and will be part of the broader ML and tech communities at Too Good To Go. Your work will directly impact millions of users by improving our surplus food management solutions and personalizing their experience.

Tech Stack

Our models are written in Python, supported by SQL to retrieve data. Our models are built, evaluated, and productionised using our MLOps team's platform, which is based on Metaflow. The full Machine Learning stack includes: GitHub, Jenkins, Docker, Airflow, OpenSearch, and Redshift.

Responsibilities

Working on researching, building, and designing different machine-learning models for marketing personalization.
Running experiments, evaluating, and using the results to improve machine learning models and algorithms.
Working end-to-end to solve problems with a product and customer-oriented mindset.
Building and deploying models in production.
Involvement in developing statistical models.
Collaborating with the rest of the team to improve our product and solve customer problems.

The Ideal Candidate

Has established experience within a similar role.
Experience using Python and deploying to production.
First-hand experience with ML libraries, frameworks, and tools, such as PyTorch, TensorFlow, Scikit-learn, Prophet, DeepAR, etc.
Degree educated within a technical field (Computer Science or equivalent engineering degree).
Experience in a cloud environment (AWS, Google Cloud, or Azure).
Bonus: experience with dbt, Snowflake, Airflow, or Metaflow; experience in complex ML system design; and experience in statistical hypothesis testing.

What We Offer

Develop and maintain the backbone of our personalization engine, which is used by millions of users every day to support their efforts to combat food waste.
An opportunity to work in a global social-impact company and certified B Corporation where you can see a real and tangible impact in your role.
To be an integral member of our defined product teams. We are eager for you to make an impact and contribute to the product scope and development; your insights are valuable, and we are here to listen.
We trust in our employees and encourage an autonomous environment that provides several opportunities for employees to contribute, develop, and take ownership of their work in a way that works for them.
To be part of an international company, with over 1,300+ colleagues across 20 countries.

Our Values

We win together: Food waste is a big beast to fight. We can do it if we win together as Waste Warriors with no ego. We believe in a #oneteam.
We raise the bar: We always push for more. We work smart, smash barriers, and elevate one another.
We keep it simple: Our ambitions are bold but our solutions are simple.
We build a legacy: We’re proud of the change we’re driving and want it to last.
We care: We always look out for each other. Caring is also about the way we do business. We do the right thing.

How To Apply

We take recruitment very seriously, so please carefully read everything we have written above.
Please also check our website and international media in order to get a good overview of Too Good To Go.
Please submit your CV and Cover letter in English.
Please note that we only accept applications coming through our platform. No CV or Cover Letter will be accepted by email or LinkedIn direct messaging.

Job Ref: #LI-TC1

#Li-Hybrid

A Movement for Everyone
We want to inspire and empower everyone to fight food waste together. With that mission, it’s only natural that we want to build a diverse and inclusive team of highly capable individuals who are passionate about doing things in a better way. We strongly believe we all excel and are more creative when we’re allowed to be ourselves, and we’re committed to a culture where all of us belong.
We are an equal opportunity employer and all employment is decided on the basis of qualifications, merit and business need. If you need reasonable accommodation at any point in the application or interview process, please let us know.

","hiringOrganization":{"@type":"Organization","name":"Too Good To Go","sameAs":"https://toogoodtogo.org/"},"jobLocation":{"@type":"Place","address":{"@type":"PostalAddress","addressLocality":"København, Hovedstaden, Denmark","addressCountry":"Denmark","addressRegion":"Europe"}}}},{"@type":"ListItem","position":30,"item":{"@type":"JobPosting","title":"Senior Machine Learning Engineer, Risk Data Mining - USDS","datePosted":"2025-09-18","description":"The USDS-Platform and Community Integrity (PaCI) team is missioned to:
\n- Protect U.S. TikTok users, including and beyond content consumers, creators, advertisers;
\n- Secure platform health and community experience authenticity;
\n- Build infrastructures, platforms and technologies, as well as to collaborate with many cross-functional teams and stakeholders.
\nThe PaCI team works to minimize the damage of inauthentic behaviors on TikTok platforms, covering multiple classical and novel community and business risk areas such as account integrity, engagement authenticity, anti-spam, API abuse, growth fraud, live streaming security and financial safety, etc. In this team, you'll have a unique opportunity to have first-hand exposure to the strategy of the company in key security initiatives, especially in building scalable and robust, intelligent and privacy-safe, secure, and product-friendly systems and solutions. Our challenges are not some regular day-to-day technical puzzles -- You'll be part of a team that's developing novel solutions to first-seen challenges of a non-stop evolution of a phenomenal product eco-system. The work needs to be fast, transferrable, while still down to the ground to make quick and solid differences.
\n
\nIn order to enhance collaboration and cross-functional partnerships, among other things, at this time, our organization follows a hybrid work schedule that requires employees to work in the office 3 days a week, or as directed by their manager/department. We regularly review our hybrid work model, and the specific requirements may change at any time.
\n
\nResponsibilities:
\n- Build machine learning solutions to respond to and mitigate business risks in TikTok products/platforms. Such risks include and are not limited to abusive accounts, fake engagements, spammy redirection, scraping, fraud, etc.
\n- Improve modeling infrastructures, labels, features and algorithms towards robustness, automation and generalization, reduce modeling and operational load on risk adversaries and new product/risk ramping-ups.
\n- Uplevel risk machine learning excellence on privacy/compliance, interpretability, risk perception and analysis.","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":31,"item":{"@type":"JobPosting","title":"Senior Machine Learning Engineer","datePosted":"2025-09-18","description":"

Company Description

About Grab and Our Workplace

Job Description

Get To Know The Team:

In the Mobility Data Science team you are at the core and center of Grab's ride hailing business. We are responsible for building and serving AI models to empower our pax' ride hailing experience in Grab.
Our primary goals are to enhance our passenger experience, and drive decision-making that contributes to user growth and platform efficiency
We leverage your mathematical modeling, statistical analysis, machine learning algorithms, and programming proficiency to drive data-driven decisions and help us conquer unique business challenges in the ride-hailing industry

Get To Know The Role:

Explore and extract insights from massive dataset of geospatial, behavioral, economic, and tens of millions of interactions of our passengers on our platform that can improve passenger experience and network efficiency
Contribute to solving key business problems such as user experience, user growth, demand and supply balancing, and service differentiation.
Develop and implement machine learning models to predict ride demand, passenger preferences, passenger cancellation/churn and improve the overall efficiency of the ride-hailing system.
Continues improvement through iterative model enhancement and A/B testing
Collaborate cross-functionally with software engineers, product managers, and operational teams to translate business needs into data solutions, implementing and deploying these solutions at scale.
Contribute to team's innovation and IP creation

Qualifications

Ph.D. graduate, or Master's Degree graduate with at least 3 years of experience, in Machine Learning, Statistics, Applied Mathematics, Computer Science, Economics, Operations Research, or a related field
Extensive proven experience as a Data Scientist, preferably within the ride-hailing or related industries.
Deep understanding of machine learning, deep learning, data mining, algorithmic foundations of optimization. Experience with machine learning framework (Tensorflow, pytorch, etc)
Proficient in one or more of the following programming languages: Python, Scala.
Self-motivated, independent learner, and willing to share knowledge with team members
Excellent interpersonal and communication skills to foster collaboration with team members and effectively articulate insights to stakeholders.
Ability to thrive in a dynamic, fast-paced work environment, managing multiple priorities simultaneously.

Additional Information

Life At Grab

We care about your well-being at Grab, here are some of the global benefits we offer:

We have your back with Term Life Insurance and comprehensive Medical Insurance.
With GrabFlex, create a benefits package that suits your needs and aspirations.
Celebrate moments that matter in life with loved ones through Parental and Birthday leave, and give back to your communities through Love-all-Serve-all (LASA) volunteering leave
We have a confidential Grabber Assistance Programme to guide and uplift you and your loved ones through life's challenges.
Balancing personal commitments and life's demands are made easier with our FlexWork arrangements such as differentiated hours

What We Stand For At Grab

We are committed to building an inclusive and equitable workplace that provides equal opportunity for Grabbers to grow and perform at their best. We consider all candidates fairly and equally regardless of nationality, ethnicity, race, religion, age, gender, family commitments, physical and mental impairments or disabilities, and other attributes that make them unique.

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About Us

Observe.AI enables enterprises to transform how they connect with customers - through AI agents and copilots that engage, assist, and act across every channel. From automating conversations to guiding human agents in real time to uncovering insights that shape strategy, Observe.AI turns every interaction into a driver of loyalty and growth. Trusted by global leaders, we’re creating a future where every customer experience is smarter, faster, and more impactful.

Why Join Us

At our core, we are shaping how AI transforms real-world challenges in the contact center space. As part of our world-class ML team, you’ll work on developing cutting-edge LLM-powered solutions & Agentic AI, building end-to-end processing pipelines, and handling production challenges at scale—millions of interactions daily—while shaping the future of AI-powered contact centers.

If you are truly an engineer at heart, excited about turning breakthroughs in multi-agent systems, LLMs, NLP, and ML into practical outcomes through applied research, and building scalable production systems to create real product impact, you will feel right at home at Observe.AI. You’ll also have the opportunity to publish in top conferences, and influence Observe.AI’s product and platform strategy.

Beyond the tech, you’ll join a collaborative, mission-driven culture where innovation, impact, and fun go hand in hand. We value curiosity, collaboration, and the courage to push boundaries.

What you’ll be doing

Design & develop state-of-the-art LLM-powered AI capabilities and Agentic AI/ Multi-agent systems end-to-end, from ideation to production for Observe.AI’s product offerings, in a fast-paced startup environment.
Work with cutting-edge tools and technologies in Machine Learning, Deep Learning & Natural Language Processing, including LLMs and LLM-powered technologies/ paradigms, including Agentic AI.
Build/ maintain highly scalable production systems that power AI capabilities on Observe.AI product/ platform.
Optimize ML models and processing pipelines for performance, cost-effectiveness, and scale.
Work with a world-class ML team in building exciting stuff, mentor juniors, and influence peers/ stakeholders.
Collaborate cross-team with engineers, product managers, customer-facing teams, and customers to understand pain points and business opportunities to build the right solution for the right problem.
Keep up-to-date with the latest ML/ DL/ NLP literature and influence the technological evolution of Observe.AI platform.
Contribute to the community through tech blogs and publishing papers in ML/ NLP conferences like EMNLP, ACL, etc.

What you’ll bring to the role

Bachelor’s or Master’s degree in Computer Science or related disciplines from a top-tier institution with exposure to ML/ DL/ NLP/ NLU.
An engineering mindset with the competencies of an applied scientist.
3+ years of industry experience in building large-scale NLP/ NLU systems, with recent experience in building LLM-powered applications and Agentic systems.
Strong understanding of the fundamentals of ML and NLP/ NLU, and practical aspects of building ML systems in production; backed by extensive hands-on experience in building/ scaling customer-facing ML/ NLP/ NLU applications.
Good understanding of recent advances in building LLM-powered applications, and multi-agent systems at scale.
Excellent implementation skills in Python and Machine Learning Frameworks such as Pytorch, Tensorflow, HuggingFace, etc., and deploying/ maintaining scalable machine learning systems in production.
Ability to provide thought leadership in one or more technical areas of interest to Observe.AI, and influence product development
Excellent communication, collaboration skills, and presentation skills.
Experience with Spoken Language Understanding is a plus
Published papers in top NLP/ NLU conferences or workshops are a plus
Relevant open-source contributions are a plus.

Perks & Benefits

Excellent medical insurance options and free online doctor consultations
Yearly privilege and sick leaves as per Karnataka S&E Act
Generous holidays (National and Festive) recognition and parental leave policies
Learning & Development fund to support your continuous learning journey and professional development
Fun events to build culture across the organization
Flexible benefit plans for tax exemptions (i.e. Meal card, PF, etc.)

Our Commitment to Inclusion and Belonging

Observe.AI is an Equal Employment Opportunity employer that proudly pursues and hires a diverse workforce. Observe AI does not make hiring or employment decisions on the basis of race, color, religion or religious belief, ethnic or national origin, nationality, sex, gender, gender identity, sexual orientation, disability, age, military or veteran status, or any other basis protected by applicable local, state, or federal laws or prohibited by Company policy. Observe.AI also strives for a healthy and safe workplace and strictly prohibits harassment of any kind.

We welcome all people. We celebrate diversity of all kinds and are committed to creating an inclusive culture built on a foundation of respect for all individuals. We seek to hire, develop, and retain talented people from all backgrounds. Individuals from non-traditional backgrounds, historically marginalized or underrepresented groups are strongly encouraged to apply.

If you are ambitious, make an impact wherever you go, and you're ready to shape the future of Observe.AI, we encourage you to apply. For more information, visit www.observe.ai.

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Real is a fast-growing national real estate brokerage powered by technology. Real is currently operating in all U.S. states, Canada, and the District of Columbia. Founded in 2014, Real is a trailblazer in the Residential Real Estate industry, as we lead the disruption with our cutting-edge technology platform. We are on a mission to revolutionize the home-buying and selling process, making agents' lives better while creating lucrative financial opportunities for them.

For more information, visit https://www.onereal.com/

Location: India - Remote. MUST be based in the India to be considered.
Work Schedule: 2:30 PM TO 11:30PM IST

Availability: Must be able to join within 45 days of offer.

Job Summary:

We are seeking a skilled and motivated Senior Machine Learning Engineer to join our R&D Team at Real. The ideal candidate will have a strong foundation in machine learning and artificial intelligence, with hands-on experience in implementing these technologies to solve real-world problems. In this role, you will work transversely across the company, embedding AI-driven solutions into various facets of our business, including operations, customer experience, and product development.

Duties/Responsibilities

Design, develop, and deploy AI/ML models to enhance real estate operations, customer experience, and product innovation.
Work closely with various teams (e.g., operations, marketing, product development) to identify and prioritize opportunities for AI integration.
Build and maintain scalable AI systems using Python and relevant frameworks (e.g., TensorFlow, PyTorch, scikit-learn).
Stay informed about the latest trends and advancements in AI/ML to drive innovation and maintain competitive advantage.
Troubleshoot, optimize, and refine AI models to ensure high performance, reliability, and accuracy in production environments.
Maintain thorough documentation of models, processes, and results; communicate findings and progress to stakeholders.

Required Skills/Abilities:

Strong programming skills in Python and familiarity with relevant AI/ML libraries (e.g., TensorFlow, PyTorch, scikit-learn).
Solid understanding of machine learning algorithms, statistical analysis, and data modeling techniques.
Proficiency in data manipulation and analysis using tools such as Pandas, NumPy, and SQL.
Ability to identify complex problems, analyze options, and implement effective solutions in a dynamic environment.
Excellent interpersonal skills, with the ability to communicate technical concepts to non-technical stakeholders effectively.
Willingness to learn and adapt to new technologies and methodologies as the field of AI/ML evolves.
Experience in managing multiple projects simultaneously, with a focus on meeting deadlines and delivering high-quality work.

Education And Experience:

Minimum of 2 years of experience working with Python in production environments.
At least 5 years of experience in the AI/ML domain. An academic research background in AI/ML is also acceptable.
Bachelor's degree in Technology or related field.

Must-Have: Ability to truly encompass our Company Core Values

Work Hard. Be Kind
“We” are bigger than “me”
Tech X Humanity

Physical Requirements:

Sit for long periods of time

Real is proud to be an equal opportunity workplace employer. We are committed to equal employment opportunities regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability, gender identity, or Veteran status.

#LI-SP1

","hiringOrganization":{"@type":"Organization","name":"Real","sameAs":"https://onereal.com/"},"jobLocation":{"@type":"Place","address":{"@type":"PostalAddress","addressLocality":"India (Remote)","addressCountry":"India","addressRegion":"Asia/Pacific"}}}},{"@type":"ListItem","position":34,"item":{"@type":"JobPosting","title":"Senior Machine Learning Engineer","datePosted":"2025-09-18","description":"

At Medtronic you can begin a life-long career of exploration and innovation, while helping champion healthcare access and equity for all. You’ll lead with purpose, breaking down barriers to innovation in a more connected, compassionate world.

A Day In The Life

Our Global Diabetes Capability Center in Pune is expanding to serve more people living with diabetes globally. Our state-of-the-art facility is dedicated to transforming diabetes management through innovative solutions and technologies that reduce the burden of living with diabetes.
In this role as a Senior Machine Learning Engineer in the Digital Technology team, you will collaborate with data scientists and stakeholders to understand business requirements and translate them into machine learning solutions.

This role offers a dynamic opportunity to join Medtronic's Diabetes business. Medtronic has announced its intention to separate the Diabetes division to promote future growth and innovation within the business and reallocate investments and resources across Medtronic, subject to applicable information and consultation requirements. While you will start your employment with Medtronic, upon establishment of SpinCo or the transition of the Diabetes business to another company, your employment may transfer to either SpinCo or the other company, at Medtronic's discretion and subject to any applicable information and consultation requirements in your jurisdiction.

Responsibilities may include the following and other duties may be assigned:

Design, develop, and implement machine learning models and algorithms to solve complex business problems.
Use software design principles to develop production ready code.
Collect, preprocess, and analyze large datasets to train and evaluate machine learning models.
Optimize and fine-tune machine learning models for performance and accuracy.
Deploy machine learning models into production environments and monitor their performance.
Develop processes and tools to monitor and analyze model performance and data accuracy.
Stay up to date with the latest advancements in machine learning and apply them to improve existing models and algorithms.
Collaborate with cross-functional teams to integrate machine learning solutions into existing systems and workflows.
Document and communicate machine learning solutions, methodologies, and results to technical and non-technical stakeholders.
Mentor and provide guidance to junior Machine Learning Engineers.

Required Knowledge And Experience:

Bachelor’s degree from an accredited institution in a technical discipline such as the sciences, technology, engineering, or mathematics
5+ years of industry experience in writing production level, scalable code (e.g. in Python)
4+ years of experience with one or more of the following machine learning topics: classification, clustering, optimization, recommendation system, deep learning
4+ years of industry experience with distributed computing frameworks such as PySpark
4+ years of industry experience with popular ml frameworks such as Spark MLlib, Keras, Tensorflow, PyTorch, HuggingFace Transformers and other libraries (like scikit-learn, spacy, genism etc.).
4+ years of industry experience with major cloud computing services like AWS or Azure or GCP
1+ years of experience in building and scaling Generative AI Applications, specifically around frameworks like Langchain, PGVector, Pinecone, Bedrock.
Experience in building Agentic AI applications.
2+ years of technical leadership leading junior engineers in a product development setting

Preferred Qualifications:

MS or Ph.D. in Computer Science, Software Engineering, Electrical Engineering, or related fields.
Proficient in containerization services
Proficient in Sagemaker to deploy the models
Experience with working in CICD framework
Experience in deploying and scaling Open source LLM Models

Physical Job Requirements

The above statements are intended to describe the general nature and level of work being performed by employees assigned to this position, but they are not an exhaustive list of all the required responsibilities and skills of this position. 

Benefits & Compensation

Medtronic offers a competitive Salary and flexible Benefits Package
A commitment to our employees lives at the core of our values. We recognize their contributions. They share in the success they help to create. We offer a wide range of benefits, resources, and competitive compensation plans designed to support you at every career and life stage.

This position is eligible for a short-term incentive called the Medtronic Incentive Plan (MIP).

About Medtronic

We lead global healthcare technology and boldly attack the most challenging health problems facing humanity by searching out and finding solutions.
Our Mission — to alleviate pain, restore health, and extend life — unites a global team of 95,000+ passionate people.
We are engineers at heart— putting ambitious ideas to work to generate real solutions for real people. From the R&D lab, to the factory floor, to the conference room, every one of us experiments, creates, builds, improves and solves. We have the talent, diverse perspectives, and guts to engineer the extraordinary.

Learn more about our business, mission, and our commitment to diversity here

","hiringOrganization":{"@type":"Organization","name":"Medtronic","sameAs":"https://www.medtronic.com/"},"jobLocation":{"@type":"Place","address":{"@type":"PostalAddress","addressLocality":"IND-MH Pune Viman Nagar, India","addressCountry":"India","addressRegion":"Asia/Pacific"}}}},{"@type":"ListItem","position":35,"item":{"@type":"JobPosting","title":"Senior Machine Learning Engineer, Ad Platforms","datePosted":"2025-09-18","description":"

Job Posting Title:

Senior Machine Learning Engineer, Ad Platforms

Req Id:

10129950

Job Description:

Technology is at the heart of Disney’s past, present, and future. Disney Entertainment and ESPN Product & Technology is a global organization of engineers, product developers, designers, technologists, data scientists, and more – all working to build and advance the technological backbone for Disney’s media business globally.

The team marries technology with creativity to build world-class products, enhance storytelling, and drive velocity, innovation, and scalability for our businesses. We are Storytellers and Innovators. Creators and Builders. Entertainers and Engineers. We work with every part of The Walt Disney Company’s media portfolio to advance the technological foundation and consumer media touch points serving millions of people around the world.

Here are a few reasons why we think you’d love working here:

Building the future of Disney’s media: Our Technologists are designing and building the products and platforms that will power our media, advertising, and distribution businesses for years to come.
Reach, Scale & Impact: More than ever, Disney’s technology and products serve as a signature doorway for fans' connections with the company’s brands and stories. Disney+. Hulu. ESPN. ABC. ABC News…and many more. These products and brands – and the unmatched stories, storytellers, and events they carry – matter to millions of people globally.
Innovation: We develop and implement groundbreaking products and techniques that shape industry norms, and solve complex and distinctive technical problems.

Ad Platforms is responsible for Disney’s industry-leading ad technology and products – driving advertising performance, innovation, and value in Disney’s sports, news, and entertainment content, across all media platforms.

The Ad Platform research team is under Ad Platforms and its mission is to transform advertising and Disney's Ad platform with AI and data science. We build solutions to measure and optimize every aspect of the advertising life cycle. Our tenant is a strong cross-domain team to deliver E2E solutions for machine learning and data science. Our team is seeking a Senior Machine Learning Engineer who will be an outstanding addition and focusing on machine learning algorithm development for addressable ad platforms. The right person for this role should be experienced in crafting implementation for either machine learning technologies or data-driven algorithms. If you are someone who is proactive and innovative in these domains, this is a phenomenal role for you!

Responsibilities:

Drive ground-breaking innovation and apply state of the art AI and machine learning in a variety of areas to enhance every aspect of advertising, including inventory forecasting, ad experience, ad pacing, pricing, targeting, and efficient ad delivery.
Invent and iterate novel solutions for complex ad challenges with fast turnaround.
Lead the ad algorithm architecture design and iteration of the advertising system.
Develop scalable and efficient approaches for large scale data analysis and model development.
Build and experiment new algorithms and models end-to-end, from production rollout to continuous optimization.
Collaborate with engineering teams, product managers, and program managers in an open and creative environment.

Basic Qualifications

5+ years of relevant engineering experience working at leading technology companies.
Strong knowledge of and experience implementing AI/ML technologies, mathematics and statistics.
Proficient in Java, Python, Scala, large scale ML/DL platforms and processing tech stack.
Passionate about understanding the ad business, applying advanced research to relevant business scenarios, and seeking innovation opportunities to enhance business effectiveness.
Passionate about technology, open to interdisciplinary collaborations, and experienced in building data-driven services and applications.
A proven track record of thriving in a fast-paced, data-driven, and collaborative work environment is required.

Preferred Qualifications:

Experience in large scale machine learning.
Experience in LLM and GenAI.
Experience with CTR/CVR model, generative AI.
Experience with feature store, audience segmentation and MLOps
Experience with Tensorflow, Kubeflow or Sagemaker
Experience in the advertising, digital video advertising, or digital marketing domain
Bachelor's degree in computer science, Information Systems or related equivalent experience.
Master’s degree in computer science, Information Systems or related equivalent experience.
Primary City, State, Region, Postal Code:

Required Education:

Preferred Education:

#Disneytech

The hiring range for this position in WA is $145,400.00 to $195,000.00 per year and in CA is $138,900.00 to $203,900.00 per year. The base pay actually offered will take into account internal equity and also may vary depending on the candidate’s geographic region, job-related knowledge, skills, and experience among other factors. A bonus and/or long-term incentive units may be provided as part of the compensation package, in addition to the full range of medical, financial, and/or other benefits, dependent on the level and position offered.

Job Posting Segment:

Ad Platforms

Job Posting Primary Business:

AP - Software Engineering

Primary Job Posting Category:

Machine Learning

Employment Type:

Full timeSeattle, WA, USA

Alternate City, State, Region, Postal Code:

USA - CA - 2450 Broadway, USA - CA - Market St

Date Posted:

2025-08-27","hiringOrganization":{"@type":"Organization","name":"The Walt Disney Company","sameAs":"https://thewaltdisneycompany.com/"},"jobLocation":{"@type":"Place","address":{"@type":"PostalAddress","addressLocality":"USA - WA - 925 4th Ave, United States","addressCountry":"United States","addressRegion":"North America"}}}},{"@type":"ListItem","position":36,"item":{"@type":"JobPosting","title":"Senior Machine Learning Engineer","datePosted":"2025-09-18","description":"

A Day In The Life

Responsibilities may include the following and other duties may be assigned:

Design, develop, and implement machine learning models and algorithms to solve complex business problems.
Use software design principles to develop production ready code.
Collect, preprocess, and analyze large datasets to train and evaluate machine learning models.
Optimize and fine-tune machine learning models for performance and accuracy.
Deploy machine learning models into production environments and monitor their performance.
Develop processes and tools to monitor and analyze model performance and data accuracy.
Stay up to date with the latest advancements in machine learning and apply them to improve existing models and algorithms.
Collaborate with cross-functional teams to integrate machine learning solutions into existing systems and workflows.
Document and communicate machine learning solutions, methodologies, and results to technical and non-technical stakeholders.
Mentor and provide guidance to junior Machine Learning Engineers.

Required Knowledge And Experience:

Bachelor’s degree from an accredited institution in a technical discipline such as the sciences, technology, engineering, or mathematics
5+ years of industry experience in writing production level, scalable code (e.g. in Python)
4+ years of experience with one or more of the following machine learning topics: classification, clustering, optimization, recommendation system, deep learning
4+ years of industry experience with distributed computing frameworks such as PySpark
4+ years of industry experience with popular ml frameworks such as Spark MLlib, Keras, Tensorflow, PyTorch, HuggingFace Transformers and other libraries (like scikit-learn, spacy, genism etc.).
4+ years of industry experience with major cloud computing services like AWS or Azure or GCP
1+ years of experience in building and scaling Generative AI Applications, specifically around frameworks like Langchain, PGVector, Pinecone, Bedrock.
Experience in building Agentic AI applications.
2+ years of technical leadership leading junior engineers in a product development setting

Preferred Qualifications:

MS or Ph.D. in Computer Science, Software Engineering, Electrical Engineering, or related fields.
Proficient in containerization services
Proficient in Sagemaker to deploy the models
Experience with working in CICD framework
Experience in deploying and scaling Open source LLM Models

Benefits & Compensation

This position is eligible for a short-term incentive called the Medtronic Incentive Plan (MIP).

About Medtronic

Learn more about our business, mission, and our commitment to diversity here

","hiringOrganization":{"@type":"Organization","name":"Medtronic","sameAs":"https://www.medtronic.com/"},"jobLocation":{"@type":"Place","address":{"@type":"PostalAddress","addressLocality":"IND-MH Pune Viman Nagar, India","addressCountry":"India","addressRegion":"Asia/Pacific"}}}},{"@type":"ListItem","position":37,"item":{"@type":"JobPosting","title":"Senior Machine Learning Engineer","datePosted":"2025-09-18","description":"

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

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

Role: Senior Machine Learning Engineer
Experience Level: 3 to 6 Years
Locations: Mumbai, Bangalore & Trivandrum

About The Role:

You will be working as a Senior Machine Learning Engineer within the healthcare domain, working on and delivering projects that are running across multiple geographies, helping healthcare organizations achieve their business goals with the use of data ingestion technologies, cloud services & DevOps. You will be working with teams from other specialties such as Cloud engineering, Software engineering, and Data engineering to create platforms, solutions, and applications that cater to the latest trends in the healthcare industry such as digital diagnosis, software as a medical product, and AI marketplace, amongst others.

Role & Responsibilities:

Developing high-level solution architectures and working with our offshore team of big-data engineers and machine learning engineers to build, test, and assess models that predict and optimize business outcomes based on the client’s success criteria.
Develop sophisticated yet simple interpretations and communicate insights to clients that lead to quantifiable business impact.
Building deep relationships with clients by understanding their stated but more importantly, latent needs.
Working hands-on with the delivery teams in building solutions in the healthcare domain (Provider, Payer, and Pharma)
Working closely with the offshore delivery managers to ensure seamless communication and delivery cadence.Researching and identifying sales opportunities, generating leads, target identification, and classification
Serve as a mentor or guide for junior resources/freshers.
Lead the technical discussion with the clients regarding updates/risks/blockers, etc. Fluent in communication

Must Have Skills:

Hands-on experience in developing and deploying models in computer vision or NLP or both
Experience or exposure to LLMs, Gen AI/ prompt engineering (RAG architecture)
Work with MLOps frameworks and tools to train and interpret the ML models for business stakeholders
Knowledge of Cloud-environments like GCP/AWS and ML frameworks like TensorFlow/PyTorch etc
Ability to think creatively and work well both as part of a team and as an individual contributor
Critical eye for the quality of data and a strong desire to get it right.
A pleasantly forceful personality and charismatic communication style.
Someone who will raise the average effectiveness of the team. In short, we are looking for a “Difference Maker”.
Experience and understanding of ML Ops

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

","hiringOrganization":{"@type":"Organization","name":"Quantiphi","sameAs":"https://www.linkedin.com/company/quantiphi/"},"jobLocation":{"@type":"Place","address":{"@type":"PostalAddress","addressLocality":"IN KL Trivandrum, India","addressCountry":"India","addressRegion":"Asia/Pacific"}}}},{"@type":"ListItem","position":38,"item":{"@type":"JobPosting","title":"Senior Machine Learning Engineer","datePosted":"2025-09-18","description":"

Location(S):

United States of America

City/Cities:

Atlanta

Travel Required:

00% - 25%

Relocation Provided:

Job Posting End Date:

October 10, 2025

Shift:

Job Description Summary:

Location: Atlanta, GA (Global HQ) - hybrid, onsite 3 days/week

The Global Equipment Platforms (GEP) team is seeking an exceptional and forward-thinking AI & Cloud Innovation Engineer to spearhead the exploration, prototyping, and strategic integration of cutting-edge Artificial Intelligence and advanced cloud capabilities for The Coca-Cola Company's global fleet of 17MM+ connected equipment. Reporting to the AI & Digital Innovation Lead within GEP Digital, Data, & AI, this individual contributor role is pivotal in transforming the insights generated by our Data Scientists into tangible, deployed capabilities that reduce operating expenses, increase revenue, and provide unprecedented real-time market understanding.

You will be responsible for researching, experimenting with, and building proofs-of-concept (POCs) utilizing nascent AI technologies (e.g., advanced Generative AI applications, cutting-edge computer vision techniques, responsible AI frameworks, sophisticated AI Agents) and novel cloud architectures (e.g., edge computing for IoT, serverless AI patterns, highly distributed compute models on Azure). This role demands deep technical expertise in both AI and cloud environments, coupled with a relentless curiosity and a proven ability to translate abstract ideas into tangible, demonstrable prototypes. Your work will directly inform the future roadmap of our Unified IoT solution, ensuring we can strategically leverage breakthroughs to further reduce TCO, increase transactions, and generate unparalleled real-time insights from our KO Operating System (KOS)-powered devices across a multi-tenant global landscape.

Key Responsibilities:

AI/ML Model Implementation & MLOps (40%):

Design, develop, and maintain robust, scalable MLOps pipelines for deploying, monitoring, retraining, and versioning machine learning models, AI Agents, and computer vision algorithms.
Implement automated CI/CD processes for AI artifacts, ensuring rapid and reliable deployment of models into production environments (e.g., Azure ML, Azure Kubernetes Service).
Work hands-on to containerize (e.g., Docker) and orchestrate (e.g., Kubernetes) AI services for efficient resource utilization and high availability across the global equipment fleet.
Develop and manage API endpoints for AI models, ensuring secure, low-latency, and high-throughput inference services for consumption by applications and other systems.

AI Infrastructure & Ecosystem Integration (25%):

Collaborate with Lead Data Engineers and Digital Technology Solutions (IT) to provision, configure, and optimize cloud-based AI infrastructure (e.g., GPU clusters, specialized compute instances) on Azure.
Integrate AI capabilities seamlessly into existing GEP applications and platforms, including remote equipment management tools, content management systems, marketing solutions, and analytics dashboards.
Design and implement data contracts and integration patterns between AI services and the core IoT platform, ensuring efficient data flow for real-time inference and model updates.
Ensure the AI solutions are generic enough to support varied global market needs and can operate across different equipment types (dispense, vend, cooler, racks).

Advanced AI Exploration & Transformation (20%):

Research, prototype, and engineer solutions for emerging AI technologies, including the operationalization of AI Agents for autonomous decision-making and advanced computer vision algorithms for real-time insights from equipment.
Drive the \"transformation\" aspect by actively enabling internal teams, bottlers, and OEMs to adopt and leverage AI-powered features, demonstrating their value and providing technical enablement.
Work closely with Data Scientists to transition experimental models into production-grade solutions, ensuring scalability, reliability, and maintainability.
Identify opportunities to apply AI to reduce equipment TCO, increase transactions, and provide deeper market insights, turning the 17MM+ pieces of equipment into intelligence assets.
Research, prototype, and evaluate cutting-edge AI technologies (e.g., Generative AI, Edge AI, Computer Vision on KOS) to identify new opportunities, working closely with the Lead AI Engineer to establish feasibility for scalable production deployment and with the Product Owner to assess potential for new product features.
Collaborate with Data Scientists on novel algorithmic approaches, providing expertise on implementation challenges and opportunities for product ionization.

Performance Monitoring & Optimization (15%):

Implement comprehensive monitoring, logging, and alerting for deployed AI models, tracking performance metrics (e.g., latency, throughput, error rates), model drift, and data quality issues in production.
Proactively identify bottlenecks and optimize the performance and cost-efficiency of AI inference and retraining pipelines.
Establish best practices for model retraining strategies, including trigger conditions, data versioning, and A/B testing in production.
Ensure the AI solutions are designed to take advantage of future connected device technology breakthroughs (e.g., LoRaWAN) and hardware advancements.

Key Deliverables:

Robust, scalable, and highly available MLOps pipelines for the GEP AI ecosystem.
Production-ready deployed AI/ML models (e.g., predictive maintenance, computer vision, AI Agents) delivering measurable business value.
Optimized AI inference services with clear APIs for application integration.
Comprehensive monitoring and alerting frameworks for deployed AI solutions.
Documented AI engineering best practices, architecture patterns, and deployment guides.
Successful enablement and adoption of AI-powered features by internal and external stakeholders.

Decision Rights:

Technical design and implementation details for MLOps pipelines and AI model serving infrastructure.
Selection of specific AI engineering tools and libraries (within approved Azure ecosystem guidelines).
Optimization strategies for AI model performance, cost, and reliability in production.

Required Experience & Qualifications:

Bachelor's degree in Computer Science, Software Engineering, Data Science, or a related quantitative field. Master's or Ph.D. preferred.
4+ years of hands-on experience in AI/ML engineering, MLOps, or productionizing machine learning models in cloud environments.
Expert-level proficiency in designing, building, and operating production-grade AI/ML pipelines on Microsoft Azure (e.g., Azure Machine Learning, Azure Kubernetes Service, Azure Functions, Azure Databricks).
Strong software engineering background with extensive experience in Python, including developing robust, production-quality code and APIs.
Proficiency with containerization technologies (Docker) and orchestration platforms (Kubernetes).
Experience with deep learning frameworks (e.g., TensorFlow, PyTorch) and deploying models trained with these frameworks.
Solid understanding of cloud infrastructure concepts, networking, and security best practices relevant to AI deployments.
Experience with Git and CI/CD tools (e.g., Azure DevOps, GitHub Actions).
Familiarity with IoT, telemetry data, and embedded systems (exposure to KOS or similar OS is a plus).
Proven ability to work independently and drive technical projects from conception to production.

Competencies:

Engineering Excellence: Possesses deep software engineering principles and applies them rigorously to build robust, scalable, and maintainable AI solutions.
AI Vision & Execution: Translates strategic AI concepts into practical, deployable systems, bridging research with real-world application.
Problem Solver & Innovator: Tackles complex technical challenges in AI deployment, consistently seeking and implementing innovative solutions.
Collaborative Integrator: Works effectively across diverse technical teams (Data Science, Data Engineering, IT) and with business stakeholders to ensure seamless AI integration.
Results-Driven & Accountable: Focuses on delivering tangible business value through deployed AI, taking ownership of the end-to-end operational success of solutions.
Continuous Learner: Stays abreast of the rapidly evolving AI landscape and proactively adopts new technologies and best practices.

Success Is Measured By:

Productionized AI Solutions: Number and diversity of AI/ML models, AI Agents, or computer vision solutions successfully deployed and operating in production.
Operational Performance: Uptime, latency, and throughput of deployed AI services; adherence to defined SLAs.
Cost Efficiency: Optimization of compute and storage costs for AI workloads in production.
Business Impact: Measurable contribution to TCO reduction, revenue uplift, and enhancement of real-time market insights via AI-powered features.
Deployment Velocity: Reduction in time from model readiness to production deployment.
Model Reliability: Reduction in production incidents related to AI model serving and performance.
What We Can Do for You
Iconic & Innovative Brands: Our portfolio represents over 250 products with some of the most popular brands in the world, including Coca-Cola, Simply, Fairlife & Topo Chico.
Expansive & Diverse Customers: We work with a diversified group of customers which range from retail & grocery outlets, theme parks, movie theatres, restaurants, and many more each day.

All persons hired will be required to verify identity and eligibility to work in the United States and to complete the required employment eligibility verification form (Form I-9) upon hire.

Skills:

Artificial Intelligence (AI), Azure Kubernetes Service (AKS), Containerization Software, Docker (Software), Git, GitHub, Machine Learning, Machine Learning Operations, Microsoft Azure Databricks, Microsoft Azure DevOps, Microsoft Azure Functions, Microsoft Azure Machine Learning

Pay Range:

$131,000 - $153,000

Base pay offered may vary depending on geography, job-related knowledge, skills, and experience. A full range of medical, financial, and/or other benefits, dependent on the position, is offered.

Annual Incentive Reference Value Percentage:

Annual Incentive reference value is a market-based competitive value for your role. It falls in the middle of the range for your role, indicating performance at target.

Our Purpose And Growth Culture:

We are taking deliberate action to nurture an inclusive culture that is grounded in our company purpose, to refresh the world and make a difference. We act with a growth mindset, take an expansive approach to what’s possible and believe in continuous learning to improve our business and ourselves. We focus on four key behaviors – curious, empowered, inclusive and agile – and value how we work as much as what we achieve. We believe that our culture is one of the reasons our company continues to thrive after 130+ years. Visit Our Purpose and Vision to learn more about these behaviors and how you can bring them to life in your next role at Coca-Cola.

We are an Equal Opportunity Employer and do not discriminate against any employee or applicant for employment because of race, color, sex, age, national origin, religion, sexual orientation, gender identity and/or expression, status as a veteran, and basis of disability or any other federal, state or local protected class. When we collect your personal information as part of a job application or offer of employment, we do so in accordance with industry standards and best practices and in compliance with applicable privacy laws.","hiringOrganization":{"@type":"Organization","name":"The Coca-Cola Company","sameAs":"https://www.coca-colacompany.com/"},"jobLocation":{"@type":"Place","address":{"@type":"PostalAddress","addressLocality":"US - GA - Atlanta, United States","addressCountry":"United States","addressRegion":"North America"}}}},{"@type":"ListItem","position":39,"item":{"@type":"JobPosting","title":"Senior Machine Learning Engineer AI Inferencing","datePosted":"2025-09-17","description":"

Company Description

Job Description

This Role is based in our Santa Clara office and requires two days in the office

PLATO (Platform Engineering and AI Technology Organization) at ServiceNow is a customer-focused innovative group building intelligent software using a variety of technology stacks to enable end-to-end, industry-leading work experiences for our customers. We are a group of people deeply invested in the success of our customers that happen to have expertise and knowledge in advanced technologies and software engineering best practices. We are data driven, structured, committed and we enjoy what we are doing. We prioritize robustness, performance and user experience over the technology stack and tools.

What you get to do in this role:

You will play a major part in building AI and Machine Learning (ML) platform that transform the user experience and workflow efficiency of enterprise services.

Your skills will enable us to build and optimize a high-performance inferencing platform, allowing our core platform to provide high quality AI solutions to our enterprise customers globally.

Utilize your expertise in Python and Golang to develop high-performance components of the AI Platform.
Collaborate with cross-functional teams to integrate AI capabilities seamlessly into workflows and user experiences.
Ensure reliability and performance of AI models by applying best practices in software engineering and AI inferencing.
Stay ahead of the curve by quickly learning emerging technologies and applying them to enhance the AI Platform.

Qualifications

To be successful in this role you 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.
Low Latency Optimization: Experience in optimizing models for low latency inference, important for real-time applications.
High Throughput Optimization: Knowledge of maximizing inference throughput.
Real-time Systems: Understanding the constraints of real-time systems on model inference.
Model Quantization and Compression: Practical experience in reducing model size and computational cost.
Proficient in prompt engineering and developing LLM based features
Experience in using AI productivity tools such as Cursor, Windsurf, etc
Minimum 5 years of experience working in Software Development role.
Proficiency in Python and Golang, with a strong grasp of software engineering principles.
Hands-on experience with prompt engineering: ability to craft, test, and optimize prompts for task accuracy and efficiency.
Demonstrated ability to thrive in fast-paced, dynamic environments.
Knowledge of unit testing, profiling, and code tuning

For positions in this location, we offer a base pay of $158,500 - $269,500, 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

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 mission of the AI Research and Development team is to provide scalable data and model driven decision making solutions to the various business functions at Robinhood. We aim to create a personalized experience for our users, by helping them discover & engage with the right products & features within Robinhood that they might find most valuable. To accelerate progress, we are also building an accessible model development platform to democratize machine learning practices throughout the company. As we embark on this exciting journey, we are looking for a Senior Machine Learning Engineer to join us to make this vision a reality.

This role is based in our Menlo Park, CA or Bellevue, WA office(s), with in-person attendance expected at least 3 days per week.

At Robinhood, we believe in the power of in-person work to accelerate progress, spark innovation, and strengthen community. Our office experience is intentional, energizing, and designed to fully support high-performing teams.

What You'Ll Do

As a Machine Learning Engineer on our team, your primary focus will be on the implementation and evaluation of machine learning algorithms through rigorous experimentation and testing methodologies. Your responsibilities will include:

AI and ML Research: Evaluate cutting technologies, including but not limited to, transformer based model architecture and large foundational models to identify solutions for Robinhood specific problems.
Model Development and Implementation: Develop and implement scalable machine learning models focusing on advanced ranking and recommendation systems, including expertise in Collaborative Filtering, Content-Based Filtering, and Hybrid models, alongside proficiency in Learning to Rank (LTR) techniques for effective prioritization. Additionally, design reinforcement learning algorithms and apply multi-armed bandit strategies to optimize decision-making in dynamic environments, balancing exploration and exploitation.
A/B Testing and Experimentation: Design and conduct A/B tests to assess the performance of different machine learning models. This includes setting up the test environment, monitoring performance, and analyzing results.
Data Analysis and Insight Generation: Analyze experimental data to extract actionable insights. Use statistical techniques to validate the findings and ensure their relevance and accuracy.
Cross-Functional Collaboration: Work closely with other engineering teams, data scientists, and the marketing team to integrate machine learning models into the product and ensure they meet business requirements. Present results to different stakeholders.
Tooling and Documentation: Build reusable libraries for common machine learning practices. Offer support and guidance to the usage of these tools. Maintain comprehensive documentation of libraries, models, experiments, and findings.

What You Bring

5+ years of applied ML experience productionizing ML models with 2+ years focused on recommendations, ranking or personalization projects.
A fervent interest in exploring and applying AI and ML technologies.
Strive to solve sophisticated engineering problems that drive business objectives.
Solid technical foundation enabling active contribution to the design and execution of projects and ideas.
Familiarity with architectural frameworks of large, distributed, and high-scale ML applications.
Hands-on experience in classical ML techniques with tabular data as well as modern techniques with sequential data
Proven experience in ML with a focus on ranking, recommendation systems, multi-objective optimization, and reinforcement learning.
Proficiency in Python, SQL, XGboost, PyTorch/TensorFlow.
Experience with Spark, Kafka, and Kubernetes is also desirable.
Ideally you have experience in the Finance sector.

What We Offer

Challenging, high-impact work to grow your career
Performance driven compensation with multipliers for outsized impact, bonus programs, equity ownership, and 401(k) matching
Best in class benefits to fuel your work, including 100% paid health insurance for employees with 90% coverage for dependents
Lifestyle wallet - a highly flexible benefits spending account for wellness, learning, and more
Employer-paid life & disability insurance, fertility benefits, and mental health benefits
Time off to recharge including company holidays, paid time off, sick time, parental leave, and more!
Exceptional office experience with catered meals, events, and comfortable workspaces.

In addition to the base pay range listed below, this role is also eligible for bonus opportunities + equity + benefits.

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 base pay 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.

Base Pay Range:

Zone 1 (Menlo Park, CA; New York, NY; Bellevue, WA; Washington, DC)$187,000—$220,000 USDZone 2 (Denver, CO; Westlake, TX; Chicago, IL)$165,000—$194,000 USDZone 3 (Lake Mary, FL; Clearwater, FL; Gainesville, FL)$146,000—$172,000 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.

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At Qualtrics, we create software the world’s best brands use to deliver exceptional frontline experiences, build high-performing teams, and design products people love. But we are more than a platform—we are the creators and stewards of the Experience Management category serving over 18K clients globally. Building a category takes grit, determination, and a disdain for convention—but most of all it requires close-knit, high-functioning teams with an unwavering dedication to serving our customers.

When you join one of our teams, you’ll be part of a nimble group that’s empowered to set aggressive goals and move fast to achieve them. Strategic risks are encouraged and complex problems are solved together, by passing the mic and iterating until the best solution comes to light. You won’t have to look to find growth opportunities—ready or not, they’ll find you. From retail to government to healthcare, we’re on a mission to bring humanity, connection, and empathy back to business. Join over 5,000 people across the globe who think that’s work worth doing.

Senior Machine Learning Engineer - CFA, Seattle

Why We Have This Role

We are looking for an engineer to bring our Machine Learning and Artificial Intelligence R&D strategy to the next level through AI Agent.
Our goal is to extend our Experience Management capabilities into “close the loop” and personal concierge use cases - powered by Experience Agent.
You should love building simple solutions to solve hard customer problems.
Crafting systems in an agile environment to withstand hyper growth and owning quality from end to end is a rewarding challenge and one of the reasons Qualtrics is such an exciting place to work!

How You’ll Find Success

Work in a supportive environment enables individual growth and achievement of team goals
Collaborate with your peers, prioritize features, and work with a sense of urgency to deliver value to our customers
Develop scalable, robust, and highly available micro services to perform simple to complex statistical analyses and build/deploy machine learning models
Implement new features and optimize existing ones to delight our customers

How You’Ll Grow

Qualtrics is a fast paced, dynamic environment where you will have the opportunity to build on and expand your experience through working on high impact projects
Work in a multi-disciplinary team to implement, tune, and productize cutting-edge machine learning models to meet the demands of our rapidly growing business
Build and maintain highly scalable data pipelines to cleanse, anonymize, measure, and index complex and multi-modal data.
You will work alongside like minded and driven technical professionals.

Things You’Ll Do

Work closely with, and incorporate feedback from other specialists, tech-ops, and product managers
Lead and engage in design reviews, architectural discussions, requirement definitions and other technical activities in diverse capacity
Attend daily stand-up meetings, collaborate with your peers, prioritize features, and work with a sense of urgency to deliver value to your customers
Finding quick ways to prototype and test possible solutions to large problems

What We’re Looking For On Your Resume

Bachelor’s degree in Computer Science or related fields.
5-8 years of experience as a Machine Learning Engineer, demonstrating a strong track record in designing, implementing, and optimizing machine learning models for real-world applications, leveraging frameworks such as TensorFlow or PyTorch.
Strong Computer Science fundamentals in algorithm design, complexity analysis, and performance
Experience in programming with at least one modern programming language such as Python, including object-oriented design
Experience with applied machine learning models and large-scale ML systems
Experience with Agent frameworks such as LangChain, Autogen etc is a plus.

What You Should Know About This Team

This team uses AI/ML research and development services for all product lines.
This team builds core machine learning infrastructure and services.
You will get the opportunity to work with other teams, and projects on a regular basis.
The scale of the problems we are solving means your impact will scale as well.

Our Team’s Favorite Perks and Benefits

$1800 Experience bonus to be used for an “Experience” of your choosing
Unlimited Sick Days
We spend 10% of our time on individual engineering growth activities every quarter
Amazing QGroup Communities; MOSAIQ, Green Team, Qualtrics Pride, Q&Able, Qualtrics Salute, and Women’s Leadership Development, which exist as places for support, allyship, and advocacy.

The Qualtrics Hybrid Work Model: Our hybrid work model is elegantly simple: we all gather in the office three days a week; Mondays and Thursdays, plus one day selected by your organizational leader. These purposeful in-person days in thoughtfully designed offices help us do our best work and harness the power of collaboration and innovation. For the rest of the week, work where you want, owning the integration of work and life.

Qualtrics is an equal opportunity employer meaning that all qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, status as a protected veteran, or any other protected characteristic.

Applicants in the United States of America have rights under Federal Employment Laws:Family & Medical Leave Act,Equal Opportunity Employment,Employee Polygraph Protection Act

Qualtrics is committed to the inclusion of all qualified individuals. As part of this commitment, Qualtrics will ensure that persons with disabilities are provided with reasonable accommodations. If reasonable accommodation is needed to participate in the job application or interview process, to perform essential job functions, and/or to receive other benefits and privileges of employment, please let your Qualtrics contact/recruiter know.

Not finding a role that’s the right fit for now? Qualtrics Insiders is the one-stop shop for all things Qualtrics Life. Sign up for exclusive access to content created with you in mind and get the scoop on what we have going on at Qualtrics - upcoming events, behind the scenes stories from the team, interview tips, hot jobs, and more. No spam - we promise! You'll hear from us two times a month max with fresh, totally tailored info - so be sure to stay connected as you explore your best role and company fit.

\n\n

For full-time positions, this pay range is for base per year; however, base pay offered within this range may vary depending on location, job-related knowledge, education, skills, and experience. A sign-on bonus and restricted stock units may be included in an employment offer. Full-time employees are eligible for medical, dental, vision, life and disability, 401(k) with match, paid time off, a wellness reimbursement, mental health benefits, and an experience bonus. For a detailed look at our benefits, visit Qualtrics US Benefits.

Washington State Annual Pay Transparency Range$175,000—$251,000 USD","hiringOrganization":{"@type":"Organization","name":"Qualtrics","sameAs":"https://www.qualtrics.com/"},"jobLocation":{"@type":"Place","address":{"@type":"PostalAddress","addressLocality":"Seattle, Washington, United States","addressCountry":"United States","addressRegion":"North America"}}}},{"@type":"ListItem","position":42,"item":{"@type":"JobPosting","title":"Senior Machine Learning Engineer","datePosted":"2025-09-17","description":"

Company Description

Job Description

What you get to do in this role:

The Advanced Technology Group (ATG) at ServiceNow is a customer-focused innovation group building intelligent software and smart user experiences using existing and latest advanced technologies to enable end-to-end, industry-leading work experiences for customers. We are a group of researchers, applied scientists, engineers, and product managers with a dual mission. We build and evolve the AI platform, and partner with teams to build products and end-to-end AI-powered work experiences. In equal measure, we lay the foundations, research, experiment, and de-risk AI technologies that unlock new work experiences in the future.

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:

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

Additional Information

Work Personas

Equal Opportunity Employer

Accommodations

Export Control Regulations

Job Description

Join the team redefining how the world experiences design.
Hey, g'day, mabuhay, kia ora, 你好, hallo, vítejte!
Thanks for stopping by. We know job hunting can be a little time consuming and you're probably keen to find out what's on offer, so we'll get straight to the point.

Where and how you can work

Our flagship campus is in Sydney. We also have a campus in Melbourne and co-working spaces in Brisbane, Perth and Adelaide. But you have choice in where and how you work—we trust our Canvanauts to choose the balance that empowers them and their team to achieve their goals.
\n
\nWhat you’d be doing in this role

As Canva scales change continues to be part of our DNA. But we like to think that's all part of the fun. So this will give you a flavor of the type of things you'll be working on when you start, which will likely evolve over time.

At the moment this role is focused on:

Provide hands-on technical support to researchers, debugging training jobs, optimising inference pipelines, and unblocking critical workflows
Develop tools and patterns that help researchers self-serve common needs, reducing repetitive support burden
Partner with platform capability teams to identify gaps in current offerings and advocate for researcher needs
Create documentation and examples that accelerate researcher onboarding and reduce time-to-productivity
Lead technical deep-dives on performance optimisation, cost reduction, and workflow efficiency for research teams\n

You’re probably a match if

You have strong Python skills and experience with ML frameworks
You’ve worked closely with or supported research/data science teams
You’re a problem solver with strong debugging chops across the ML stack
You can explain complex technical concepts to different audiences with ease
You’re customer-focused and have the patience to support a variety of users—even when it gets repetitive
You enjoy being a force multiplier—accelerating research by removing friction

About The Team

Canva’s AI Platform Group powers AI innovation across the company. Our Enablement teams act as trusted advisors and builders for researchers, helping them go from idea to production faster. We support high-impact initiatives like Project Celestial and Turkey, and are key players in onboarding new researchers around the world. Our mission? Reduce friction, optimise workflows, and elevate Canva’s AI velocity.

What’s in it for you?

Achieving our crazy big goals motivates us to work hard—and we do—but you’ll experience lots of moments of magic, connectivity and fun woven throughout life at Canva, too. We also offer a range of benefits to set you up for every success in and outside of work.

Here’s a taste of what’s on offer:
• Equity packages – we want our success to be yours too
• Inclusive parental leave policy that supports all parents & carers
• An annual Vibe & Thrive allowance to support your wellbeing, social connection, office setup & more
• Flexible leave options that empower you to be a force for good, take time to recharge and supports you personally

Check out lifeatcanva.com for more info.

Other stuff to know
\nWe make hiring decisions based on your experience, skills and passion, as well as how you can enhance Canva and our culture. When you apply, please tell us the pronouns you use and any reasonable adjustments you may need during the interview process.

We celebrate all types of skills and backgrounds at Canva—so even if you don’t feel like your skills quite match what’s listed above, we still want to hear from you!

Please note that interviews are conducted virtually.

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Company Description

Job Description

What you get to do in this role:

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:

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

Wjaisnjobs

Additional Information

Work Personas

Equal Opportunity Employer

Accommodations

Export Control Regulations

Company Description

Experian is a global data and technology company, powering opportunities for people and businesses around the world. We help to redefine lending practices, uncover and prevent fraud, simplify healthcare, deliver digital marketing solutions, and gain deeper insights into the automotive market, all using our unique combination of data, analytics and software. We also assist millions of people to realise their financial goals and help them to save time and money.

We operate across a range of markets, from financial services to healthcare, automotive, agrifinance, insurance, and many more industry segments.

We invest in people and new advanced technologies to unlock the power of data and to innovate. A FTSE 100 Index company listed on the London Stock Exchange (EXPN), we have a team of 23,300 people across 32 countries. Our corporate headquarters are in Dublin, Ireland. Learn more at experianplc.com.

Job Description

We are looking for a Senior Machine Learning Engineer to join our AI Operations & Safety team. You will ensure the secure, compliant, and responsible deployment of generative AI (GenAI) models across financial services. Reporting into the Senior Management within the team you will lead technical projects, mentor junior engineers, and collaborate with cross-functional teams to build scalable, safe, and explainable AI systems aligned with regulatory and ethical standards.

What You'Ll Do:

Contribute to the design and implementation of Responsible AI frameworks and governance policies.
Collaborate with risk, compliance, and legal teams to ensure AI systems meet regulatory and ethical standards.
Lead technical audits and documentation efforts related to AI safety, fairness, and transparency.
Architect and maintain systems for model deployment, monitoring, and lifecycle management.
Establish guardrails for model performance, explainability, and risk mitigation.
Lead incident response and root cause analysis for AI-related issues.
Develop scalable ML pipelines for model validation, evaluation, and monitoring.
Lead development of GenAI-powered solutions in domains such as fraud detection, credit risk modeling, and customer service automation.
Collaborate with product and engineering teams to integrate AI capabilities into production systems.
Provide technical leadership across the AI Operations & Safety team.
Mentor junior and mid-level engineers, encouraging innovation.
Promote best practices in MLOps, model governance, and secure AI development.

Qualifications

What You'Ll Bring:

6–8 years of experience in machine learning, data science, or software engineering.
Proficiency in Python and ML frameworks (e.g., TensorFlow, PyTorch, or scikit-learn).
Hands-on experience with MLOps tools and practices (e.g., MLflow, Kubeflow, and CI/CD for ML).
Experience with AI governance, model risk management, and regulatory compliance in financial services.
Experience leading technical projects and mentor engineering teams.
University degree in Computer Science, Engineering, Data Science, or a related field.
Excellent written and verbal English skills.

Additional Information

You Will Get:

Personal Development - career pathway for professional growth supported by learning and development programs and unlimited access to online educational training courses, learning materials and books.
Work environment - excellent work conditions with friendly environment, recognized team spirit, and fun and quality recreation time.
Social benefit package including life insurance, food vouchers, additional health insurance, monthly flex allowance and internet coverage, corporate discounts, marriage and childbirth / adoption allowance, Multisport card, Sharesave plan, Employee assistance program, а birthday gift and many other benefits!
Work-life balance - 25 days paid vacation, 1 additional day off for your birthday and extra 3 paid days for participation in Social responsibility event.
Opportunity for Flexible working hours and Home Office.

Experian is an Equal opportunity employer. Everyone can succeed at Experian and bring their whole self to work, irrespective of their gender, ethnicity, religion, colour, sexuality, physical ability or age. If you have a disability or special need that requires accommodation, please let us know at the earliest opportunity.

#Li-Hybrid

This is a hybrid remote/in-office role.

Experian Careers - Creating a better tomorrow together

Find out what its like to work for Experian by clicking here

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Affinity stitches together billions of data points from massive datasets to create a powerful, accurate representation of the world's professional relationship graph. Based on this data, we offer our users the insights and visibility they need to nurture and tap into the opportunities in their team's network.

This role is part of the AI Insights team, which owns the services that power Affinity's industry-leading relationship intelligence platform. Our team extracts and retrieves information from billions of structured and unstructured data points to deliver insights to our customers. As a Senior Machine Learning Engineer, you will collaborate with data engineers, software engineers, and product managers to shape the future of private capital's leading CRM platform. In this role, you will design and build AI systems that efficiently uncover insights from compelling business interaction data – an exciting and unique opportunity within the industry.

This is an applied machine learning position with a strong emphasis on engineering, not research. You will play a key role in advancing our ML Ops and ML Engineering capabilities.

What You’Ll Be Doing:

Take projects from ideation to production, including feature engineering, model selection, deployment, and model observability and evaluation.
Gather product requirements and translate them into robust ML system design requirements.
Work on a variety of information extraction, information storage and information retrieval problems from both structured and unstructured data sources.
Architect efficient and scalable systems to support serving inference services.
Develop reusable AI-based services — including ML models, foundation models, and agents — that will be consumed by other backend services at Affinity.
Lead complex technical initiatives and provide technical input for peers through system design reviews, code reviews, and promoting best practices.
Collaborate with cross-functional teams (product, infra, data engineer, and software engineer) and ML engineering teams to build robust, high-scale systems that underlie all of our data processing and ML Operations.

Qualifications

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 qualification. At Affinity, 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 perfectly align with the qualifications above, we encourage you to apply anyways. You may be just the right candidate for this or other roles.

Required:

5+ years of experience in software engineering and/or Machine Learning experience in applying machine learning in production, with a focus on ML Engineering and ML Ops.
Experience in the following technical areas:

Architecture design for distributed systems.
Building maintainable and testable codebases and services.
Developing ML systems, such as recommendation systems and information retrieval solutions.
Relational DB, non-relational DB, and vectorDB.
Developing AI applications powered by LLMs and/or agents.
Proficient in building services in Python and common ML frameworks, such as PyTorch and Scikit-learn.

Experience with observability tools for both online and offline evaluation and tracing for AI applications.
Demonstrated experience working with large datasets, and are comfortable with high-scale data ingestion, transformation, analysis, and prediction tools.
Experience working collaboratively with engineering, product, data, and other cross-functional teams.

Nice To Have:

Experience with developing machine learning applications at scale, from inception to driving user impact.
Familiar with serving machine learning models for streaming and batch inference at scale.
Experience with packaging, CI/CD and pipeline automation.
Good understanding of machine learning systems’ testing, benchmarking, and online monitoring.
Experience with dataset engineering, including data curation, augmentation, and synthesis, to assist ML model improvement.

Tech stack: Our ML pipeline manages multiple Python services that support various AI features, including utilizing OCR to extract information from unstructured data, serving embedding models to vectorize chunks, and ranking a list of recommendations based on relevance and user preference. We maintain the Docker images and deployment pipeline via CircleCI. Our data stack includes Spark, Python, Kafka, and Databricks.

How We Work:

Our culture is a key part of how we operate, as well as our hiring process:

We iterate quickly. As such, you must be comfortable embracing ambiguity, be able to cut through it, and deliver value to our customers.
We are candid, transparent, and speak our minds while simultaneously caring personally with each person we interact with.
We make data-driven decisions and make the best decision for the moment based on the information available.

If you’d want to learn more about our values click here.

What You'Ll Enjoy At Affinity:

We live our values: As owners, we take pride in everything we do. We embrace a growth mindset, engage in respectful candor, act as playmakers, and \"taste the soup\" by diving deep into experiences to create the best outcomes for our colleagues and clients.
Health Benefits: We cover both you and your dependents' extended health benefit premiums and offer flexible personal & sick days to support your well-being.
Retirement Planning: We offer an RRSP plan to help you plan for your future.
Learning & Development: We provide an annual education budget and a comprehensive L&D program.
Wellness Support: We reimburse monthly for things like home internet, meals, and wellness memberships/equipment to support your overall health and happiness.
Team Connection: Virtual team-building activities and socials to keep our team connected, because building strong relationships is key to success.

Please note that the role compensation details below reflect the base salary only and do not include any equity or benefits. This represents the salary range that Affinity believes, in good faith, at the time of this posting, that it will pay for the posted job.

A reasonable estimate of the current range is $113,000 to $200,000 CAD. Within the range, individual pay depends on various factors including geographical location and review of experience, knowledge, skills, abilities of the applicant.

About Affinity

With more than 3,000 customers worldwide and backed by some of Silicon Valley's best firms, Affinity has raised $120M to empower dealmakers to find, manage, and close more deals. How? Our Relationship Intelligence platform uses the wealth of data exhaust from trillions of interactions between Investment Bankers, Venture Capitalists, Consultants, and other strategic dealmakers to deliver automated relationship insights that drive over 450,000 deals every month. We are are proud to have received Inc. and Fortune Best Workplaces awards as well as to be Great Places to Work certified for the last 5 years running. Join us on our mission to make it possible for anyone to cultivate and fully harness their network to succeed.

We Use E-Verify

Our company uses E-Verify to confirm the employment eligibility of all newly hired employees. To learn more about E-Verify, including your rights and responsibilities, please visit www.dhs.gov/E-Verify.

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In Semantics, our team's mission is to create the highest-fidelity, most comprehensive offboard perception autolabels at a massive scale, serving as the foundation for training and validating the AV stack. We are an advanced ML and engineering team that leverages state-of-the-art computer vision, deep learning, and generative AI to automatically analyze driving logs, generate rich scene understanding, and power the data engine that enables Waymo to scale safely and efficiently.

In this hybrid role, you will report to a Technical Lead Manager.

You Will:

Develop and train state-of-the-art computer vision / multimodal models (e.g., Gemini) to extract the rich semantic information (e.g., object attributes, scene properties, interaction dynamics) required by the AI agent.
Design and implement a scalable AI agent framework that integrates large foundation models (e.g., Gemini) with the outputs of our perception models and internal knowledge bases.
Develop and apply Fine-tuning and Reinforcement Learning (RL) techniques to create a \"data flywheel,\" continuously improving the system's captioning and reasoning abilities through automated feedback.
Develop and prototype novel prompting strategies for Vision-Language Models (VLMs) to elicit complex, causal reasoning about driving scenarios.
Collaborate closely with the ML Infra, Perception, Behavior, and AI Foundation teams to define data requirements and integrate the captioning system into the broader ML development lifecycle.
Own the full system lifecycle, from advanced model development and prototyping to production deployment and scaling for massive data generation

You Have:

Master’s degree in Computer Science, or a related technical field.
4+ years of hands-on experience training and shipping deep learning models for computer vision tasks (e.g., detection, segmentation, video understanding) using Python and frameworks like PyTorch, JAX, or TensorFlow.
1+ years of demonstrated experience working with large language models (LLMs) or vision-language models (VLMs) in areas such as fine-tuning, prompting, or Retrieval-Augmented Generation (RAG).
Strong software engineering fundamentals, including designing scalable and reliable systems.
Experience building and managing large-scale data processing pipelines for ML training.
Proven ability to work autonomously and lead complex technical projects in a fast-paced R&D environment.

We Prefer:

PhD in Computer Science, or a related technical field.
Publication record in top-tier AI conferences (e.g., NeurIPS, ICML, ICLR, CVPR).
Hands-on experience with Reinforcement Learning, especially RLHF, RLAIF, or applying RL to language/agentic tasks.
Experience with modern techniques in self-supervised, weakly-supervised, or multi-task learning for perception.
Experience building with AI agent frameworks (e.g., LangChain, LlamaIndex) or developing autonomous agentic systems.
Familiarity with the challenges of multimodal perception in robotics or autonomous driving.
A track record of impactful cross-functional collaboration.

Waymo employees are also eligible to participate in Waymo’s discretionary annual bonus program, equity incentive plan, and generous Company benefits program, subject to eligibility requirements.

Salary Range$204,000—$259,000 USD","hiringOrganization":{"@type":"Organization","name":"Waymo","sameAs":"https://waymo.com/"},"jobLocation":{"@type":"Place","address":{"@type":"PostalAddress","addressLocality":"Mountain View, CA, USA; San Francisco, CA, USA","addressCountry":"United States","addressRegion":"North America"}}}},{"@type":"ListItem","position":48,"item":{"@type":"JobPosting","title":"Senior Machine Learning Engineer","datePosted":"2025-09-17","description":"We anticipate the application window for this opening will close on - 2 Oct 2025

A Day In The Life

In this role as a Senior Machine Learning Engineer in the Transformation team, you will collaborate with data scientists and stakeholders to understand business requirements and translate them into machine learning solutions.

This position is an exciting opportunity to work with Medtronic's Diabetes business. Medtronic has announced its intention to separate the Diabetes division to promote future growth and innovation within the business and reallocate investments and resources across Medtronic, subject to applicable information and consultation requirements. This separation provides our team with a bold opportunity to unleash our potential, enabling us to operate with greater speed and agility. As a separate entity, we anticipate leveraging increased investments to drive meaningful innovation and enhance our impact on patient care.

Responsibilities may include the following and other duties may be assigned:

Design, develop, and implement machine learning models and algorithms to solve complex business problems.
Use software design principles to develop production ready code.
Collect, preprocess, and analyze large datasets to train and evaluate machine learning models.
Optimize and fine-tune machine learning models for performance and accuracy.
Deploy machine learning models into production environments and monitor their performance.
Develop processes and tools to monitor and analyze model performance and data accuracy.
Stay up to date with the latest advancements in machine learning and apply them to improve existing models and algorithms.
Collaborate with cross-functional teams to integrate machine learning solutions into existing systems and workflows.
Document and communicate machine learning solutions, methodologies, and results to technical and non-technical stakeholders.
Mentor and provide guidance to junior Machine Learning Engineers.

Required Knowledge And Experience:

Requires a Bachelor's degree and minimum of 4 years of relevant experience OR Master's degree with a minimum of 2 years relevant experience OR PhD with 0 years relevant experience.

Preferred Qualifications:

Bachelor’s degree from an accredited institution in a technical discipline such as the sciences, technology, engineering, or mathematics
5+ years of industry experience in writing production level, scalable code (e.g. in Python)
4+ years of experience with one or more of the following machine learning topics: classification, clustering, optimization, recommendation system, deep learning
4+ years of industry experience with distributed computing frameworks such as PySpark
4+ years of industry experience with popular ml frameworks such as Spark MLlib, Keras, Tensorflow, PyTorch, HuggingFace Transformers and other libraries (like scikit-learn, spacy, genism etc.).
4+ years of industry experience with major cloud computing services like AWS or Azure or GCP
1+ years of experience in building and scaling Generative AI Applications, specifically around frameworks like Langchain, Langgraph, PGVector, Pinecone, Bedrock.
Experience in building Agentic AI applications.
2+ years of technical leadership leading junior engineers in a product development setting
MS or Ph.D. in Computer Science, Software Engineering, Electrical Engineering, or related fields.
Proficient in containerization services
Proficient in Sagemaker to deploy the models
Experience with working in CICD framework
Experience in deploying and scaling Open source LLM Models

Physical Job Requirements

The above statements are intended to describe the general nature and level of work being performed by employees assigned to this position, but they are not an exhaustive list of all the required responsibilities and skills of this position. 

The physical demands described within the Responsibilities section of this job description are representative of those that must be met by an employee to successfully perform the essential functions of this job. Reasonable accommodations may be made to enable individuals with disabilities to perform the essential functions. For Office Roles: While performing the duties of this job, the employee is regularly required to be independently mobile. The employee is also required to interact with a computer, and communicate with peers and co-workers. Contact your manager or local HR to understand the Work Conditions and Physical requirements that may be specific to each role.

Benefits & Compensation

Salary ranges for U.S (excl. PR) locations (USD):$138,400.00 - $207,600.00This position is eligible for a short-term incentive called the Medtronic Incentive Plan (MIP).The base salary range is applicable across the United States, excluding Puerto Rico and specific locations in California. The offered rate complies with federal and local regulations and may vary based on factors such as experience, certification/education, market conditions, and location. Compensation and benefits information pertains solely to candidates hired within the United States (local market compensation and benefits will apply for others).

The following benefits and additional compensation are available to those regular employees who work 20+ hours per week: Health, Dental and vision insurance, Health Savings Account, Healthcare Flexible Spending Account, Life insurance, Long-term disability leave, Dependent daycare spending account, Tuition assistance/reimbursement, and Simple Steps (global well-being program).

The following benefits and additional compensation are available to all regular employees: Incentive plans, 401(k) plan plus employer contribution and match, Short-term disability, Paid time off, Paid holidays, Employee Stock Purchase Plan, Employee Assistance Program, Non-qualified Retirement Plan Supplement (subject to IRS earning minimums), and Capital Accumulation Plan (available to Vice Presidents and above, or subject to IRS earning minimums).

Regular employees are those who are not temporary, such as interns. Temporary employees are eligible for paid sick time, as required under applicable state law, and the Employee Stock Purchase Plan. Please note some of the above benefits may not apply to workers in Puerto Rico.

Further details are available at the link below:

Medtronic benefits and compensation plans

About Medtronic

Learn more about our business, mission, and our commitment to diversity here.

It is the policy of Medtronic to provide equal employment opportunity (EEO) to all persons regardless of age, color, national origin, citizenship status, physical or mental disability, race, religion, creed, gender, sex, 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, Medtronic will provide reasonable accommodations for qualified individuals with disabilities.

If you are applying to perform work for Medtronic, Inc. (“Medtronic”) in any position which will involve performing at least two (2) hours of work on average each week within the unincorporated areas of Los Angeles County, you can find here a list of all material job duties of the specific job position which Medtronic reasonably believes that criminal history may have a direct, adverse and negative relationship potentially resulting in the withdrawal of a conditional offer of employment. Medtronic will consider for employment qualified job applicants with arrest or conviction records in accordance with the Los Angeles County Fair Chance Ordinance for Employers and the California Fair Chance Act.

","hiringOrganization":{"@type":"Organization","name":"Medtronic","sameAs":"https://www.medtronic.com/"},"jobLocation":{"@type":"Place","address":{"@type":"PostalAddress","addressLocality":"USA-GA Duluth, United States","addressCountry":"United States","addressRegion":"North America"}}}},{"@type":"ListItem","position":49,"item":{"@type":"JobPosting","title":"Senior Machine Learning Engineer, Audio Perception","datePosted":"2025-09-16","description":"

The Audio Perception team focuses on leveraging audio to provide sufficient scene understanding and driving behavior that are uniquely captured by audio. The team owns audio-related signals and supports applications across all product areas, improving key metrics like safety, rider comfort and cost. We strive to fulfill new product requests while preserving performance on existing applications as we rapidly scale to new cities.

In this hybrid role, you will report to a Technical Lead Manager.

You Will:

Support new product requests end-to-end, from problem definition to a solution that is integrated in the onboard driving system.
Streamline the model development and evaluation stack for rapid adaptation to new tasks and data.
Establish and maintain a sustainable model stack to facilitate Waymo’s scaling across multiple platforms and cities.

You Have:

Bachelor’s degree in Computer Science or a similar discipline, or an equivalent amount of deep learning experience.
5+ years of experience in Machine Learning, with a strong focus on deep learning for perception tasks.
Deep understanding of state-of-the-art ML techniques, especially those related to multi-class classification, regression, model adaptation and scarce data.
Proficiency in at least one deep learning framework (e.g. TensorFlow, PyTorch, JAX).
Proficiency in C++ and Python.

We Prefer:

Master’s degree or Ph.D in Computer Science or a similar discipline, or an equivalent amount of deep learning experience.
Experience in audio modeling or digital signal processing.
Familiarity with multi-modal systems and/or foundation models.
Experience implementing infrastructure to support model development (e.g. data processing modules).
Experience in optimizing ML models for on-device deployment and real-time performance.
Background in autonomous driving or robotics.
Familiarity with SQL.

Waymo employees are also eligible to participate in Waymo’s discretionary annual bonus program, equity incentive plan, and generous Company benefits program, subject to eligibility requirements.

Salary Range$204,000—$259,000 USD","hiringOrganization":{"@type":"Organization","name":"Waymo","sameAs":"https://waymo.com/"},"jobLocation":{"@type":"Place","address":{"@type":"PostalAddress","addressLocality":"Mountain View, CA, USA; San Francisco, CA, USA","addressCountry":"United States","addressRegion":"North America"}}}},{"@type":"ListItem","position":50,"item":{"@type":"JobPosting","title":"Senior Machine Learning Engineer","datePosted":"2025-09-16","description":"

Calling all innovators - find your future at Fiserv.

We're Fiserv, a global leader in Fintech and payments, and we move money and information in a way that moves the world. We connect financial institutions, corporations, merchants and consumers to one another millions of times a day - quickly, reliably, and securely. Any time you swipe your credit card, pay through a mobile app, or withdraw money from the bank, we're involved. If you want to make an impact on a global scale, come make a difference at Fiserv.

Job Title

Senior Machine Learning Engineer

What does a successful Senior Machine Learning Engineer do at Fiserv?
Harnesses advanced analytics and machine learning to derive AI Ops initiatives, optimizing AI operations and system performance. This role involves collaborating with cross-functional teams to identify business needs and develop data-driven solutions that enhance operational efficiency and decision-making. By deploying and maintaining AI solutions, the Senior ML Engineer ensures they operate effectively across the organization.

What You Will Do:

Develop and implement machine learning models and algorithms to optimize AI operations and enhance system performance.
Collaborate with cross-functional teams to identify business needs and translate them into data-driven solutions.
Analyze large datasets to extract actionable insights and support strategic decision-making.
Design and conduct experiments to validate model performance and improve operational processes.
Monitor and maintain AI models in production to ensure effective and efficient operation.
Communicate findings and recommendations to stakeholders through clear visualizations and presentations.

What you will need to have:

10+ years of experience in data science, focusing on AI and machine learning applications.
8+ years of experience in programming with Python, R, or Scala and using data manipulation libraries like Pandas, Numpy.
7+ years of experience working with machine learning frameworks such as TensorFlow, PyTorch, or Scikit-learn.
6+ years of experience with cloud platforms like AWS or Azure and big data technologies such as Hadoop, Spark.
Master’s or Ph.D. in Data Science, Computer Science, Statistics, or a related field, and/or equivalent military experience.

What would be great to have:

5+ years of experience designing and deploying end-to-end machine learning pipelines in production environments.
4+ years of expertise in natural language processing (NLP) and computer vision techniques.
3+ years of knowledge in reinforcement learning and its practical applications.
4+ years of experience with ML Ops tools and practices for continuous integration and deployment of machine learning models.
3+ years of familiarity with regulatory and compliance considerations for AI and machine learning solutions.

Salary Range

$127,500.00 - $204,000.00

These pay ranges apply to employees in New Jersey and New York. Pay ranges for employees in other states may differ.

It is unlawful to discriminate against a prospective employee due to the individual's status as a veteran.

For incentive eligible associates, the successful candidate is eligible for an annual incentive opportunity which may be delivered as a mix of cash bonus and equity awards in the Company’s sole discretion.

Thank you for considering employment with Fiserv. Please:

Apply using your legal name
Complete the step-by-step profile and attach your resume (either is acceptable, both are preferable).

Our Commitment To Equal Opportunity:

Fiserv is proud to be an Equal Opportunity Employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, national origin, gender, gender identity, sexual orientation, age, disability, protected veteran status, or any other category protected by law.

If you have a disability and require a reasonable accommodation in completing a job application or otherwise participating in the overall hiring process, please contact AskHR.US@fiserv.com. Please note our AskHR representatives do not have visibility to your application status. Current associates who require a workplace accommodation should refer to Fiserv’s Disability Accommodation Policy for additional information.

Note To Agencies:

Fiserv does not accept resume submissions from agencies outside of existing agreements. Please do not send resumes to Fiserv associates. Fiserv is not responsible for any fees associated with unsolicited resume submissions.

Warning About Fake Job Posts:

Please be aware of fraudulent job postings that are not affiliated with Fiserv. Fraudulent job postings may be used by cyber criminals to target your personally identifiable information and/or to steal money or financial information. Any communications from a Fiserv representative will come from a legitimate Fiserv email address.

","hiringOrganization":{"@type":"Organization","name":"Fiserv","sameAs":"https://www.fiserv.com/"},"jobLocation":{"@type":"Place","address":{"@type":"PostalAddress","addressLocality":"Alpharetta, Georgia, United States","addressCountry":"United States","addressRegion":"North America"}}}}]}

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