Remote Senior ML Engineer Jobs
Remote Senior ML Engineer jobs are in active demand across the U.S., with remote-first firms and distributed engineering teams leading hiring in tech, fintech, and healthcare AI. Employers posting remote senior ml engineer openings right now include CVS Health, Alvarez & Marsal, and Netflix. Find a role that fits below and apply directly.
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Showing 5 of 496+ Remote Senior ML Engineer jobs
ABOUT GITHUB
GitHub is the world’s leading platform for agentic software development — powered by Copilot to build, scale, and deliver secure software. Over 180 million developers, including more than 90% of the Fortune 100 companies, use GitHub to collaborate, and more than 77,000 organisations have adopted GitHub Copilot.
LOCATIONS
In this role you can work from Remote, United States
Overview
GitHub is changing the way the world builds software and we want you to help build and secure GitHub. We're looking for an experienced machine learning engineer to help design, build and deploy agentic solutions, and to conduct ad-hoc analysis, as you help protect the home of all developers.
You will be responsible for identifying new trends relating to safety, fraud and abuse on GitHub, building agentic solutions to detect this abuse at scale, identifying vulnerabilities in GitHub that lead to abuse and helping to measure the impact of our work to safeguard the platform. At GitHub, Safety and Integrity's mission is to ensure GitHub and our users' safety through fighting malware, spam and fraud, monitoring for fake accounts, countering inauthentic content, battling crypto mining, and other core areas. You will be involved in collaborations across teams within GitHub including with Copilot and setting the standard for effective and responsible use of AI for moderation and trust and safety purposes, ensuring fraud is countered, content is moderated, users are kept safe and the open-source community can flourish.
If you have a strong foundation in large language models, solid software engineering instincts, a working knowledge of online platform trust and safety issues, and an empathetic approach to collaborating with a diverse team from entry-level associates to seasoned senior contributors, then this might be the gig for you.
WHAT WE VALUE
Collaboration: We believe the best work is done together.
Empathy: We believe in putting people first.
Quality: We believe in setting the standard for excellence.
Positive Impact: We believe in making the world a better place through our work.
* Shipping: We believe in creating things for the people using them.
Responsibilities
Design, build and deploy agentic solutions that leverage large language models to detect and prevent fraud, abuse, and security threats at scale — applying LLMs to problems such as content classification and multi-step agentic investigation.
Build well-engineered, production-grade systems that run reliably against high-volume event streams, making effective use of AI coding assistants to accelerate and improve your work.
Build and operate scalable ML systems on cloud platforms (such as Azure AI Foundry) for training, deploying, and serving models and agentic solutions in production.
Evaluate and improve existing models and agentic solutions using offline evaluations (including tool-use loops and LLM-as-judge evaluation), performance metrics, and feedback from operational deployments.
Identify vulnerabilities in products that lead to abuse, and provide consultation to product teams reviewing new features.
Collaborate closely with cross-functional teams including data scientists, software engineers, product managers and content moderators to integrate agentic solutions into production systems.
* Document the systems you help build and support the technical growth of your peers.
QUALIFICATIONS
Required Qualifications
* 4+ years experience in machine learning, or related field
+ OR Bachelor's Degree in Computer Science, Software Development, Electrical or Computer Engineering, Mathematical Sciences, or related field AND 2+ years experience in machine learning, or related field
+ OR Master's Degree in Machine Learning, Computer Science, Software Development, Electrical or Computer Engineering, Mathematical Sciences, or related field
+ OR equivalent experience.
Preferred Qualifications
Strong understanding of large language models — how they work — and hands-on experience applying them at scale, ideally for classification, agentic workflows, or agents.
Strong software engineering skills, including experience building with AI coding assistants.
Experience designing or evaluating agentic systems (tool-use loops, multi-step workflows, or LLM-as-judge evaluation).
Hands-on experience building and operating classification or detection systems at scale, including handling imbalanced data and precision/recall tradeoffs.
Experience in Trust and Safety, National Security or fighting spam, malware, fraud, and threat actor activity at scale.
Experience in responsible AI.
Experience in Safety-by-Design.
Experience with managing user data and privacy.
* Solid understanding of machine learning algorithms (supervised and unsupervised learning, anomaly detection, etc.) and their practical implementation.
COMPENSATION RANGE
The base salary range for this job is USD $107,700.00 - USD $285,900.00 /Yr.
These pay ranges are intended to cover roles based across the United States. An individual's base pay depends on various factors including geographical location and review of experience, knowledge, skills, abilities of the applicant. At GitHub certain roles are eligible for benefits and additional rewards, including annual bonus and stock. These rewards are allocated based on individual impact in role. In addition, certain roles also have the opportunity to earn sales incentives based on revenue or utilization, depending on the terms of the plan and the employee's role.
This position will be open for a minimum of 3 days, with applications accepted on an ongoing basis until the position is filled.
GITHUB LEADERSHIP PRINCIPLES
GitHub values
Customer-obsessed
Ship to learn
Growth mindset
Own the outcome
Better together
Diverse and inclusive
Manager fundamentals
Model
Coach
* Care
Leadership principles
Create clarity
Generate energy
* Deliver success
WHO WE ARE
GitHub is the world’s leading AI-powered developer platform with 150 million developers and counting. We’re also home to the biggest open-source community on earth (and 99% of the world’s software has open-source code in its DNA). Many of the apps and programs you use every day are built on GitHub.
Our teams are dreamers, doers, and pioneers, leading the way in AI, driving humanitarian efforts around the globe, and even sending open source to Mars (and beyond!). At GitHub, our goal is to create the space you need to do your best work. We’re remote-first and offer competitive pay, generous learning and growth opportunities, and excellent benefits to support you, wherever you are—because we know that people flourish when they can work on their own terms.
Join us, and let’s change the world, together.
EEO STATEMENT
GitHub is made up of people from a wide variety of backgrounds and lifestyles. We embrace diversity and invite applications from people of all walks of life. We don't discriminate against employees or applicants based on gender identity or expression, sexual orientation, race, religion, age, national origin, citizenship, disability, pregnancy status, veteran status, or any other differences. Also, if you have a disability, please let us know if there's any way we can make the interview process better for you; we're happy to accommodate!
ABOUT GITHUB
GitHub is the world’s leading platform for agentic software development — powered by Copilot to build, scale, and deliver secure software. Over 180 million developers, including more than 90% of the Fortune 100 companies, use GitHub to collaborate, and more than 77,000 organisations have adopted GitHub Copilot.
LOCATIONS
In this role you can work from Remote, United States
Overview
GitHub is changing the way the world builds software and we want you to help build and secure GitHub. We're looking for an experienced machine learning engineer to help design, build and deploy agentic solutions, and to conduct ad-hoc analysis, as you help protect the home of all developers.
You will be responsible for identifying new trends relating to safety, fraud and abuse on GitHub, building agentic solutions to detect this abuse at scale, identifying vulnerabilities in GitHub that lead to abuse and helping to measure the impact of our work to safeguard the platform. At GitHub, Safety and Integrity's mission is to ensure GitHub and our users' safety through fighting malware, spam and fraud, monitoring for fake accounts, countering inauthentic content, battling crypto mining, and other core areas. You will be involved in collaborations across teams within GitHub including with Copilot and setting the standard for effective and responsible use of AI for moderation and trust and safety purposes, ensuring fraud is countered, content is moderated, users are kept safe and the open-source community can flourish.
If you have a strong foundation in large language models, solid software engineering instincts, a working knowledge of online platform trust and safety issues, and an empathetic approach to collaborating with a diverse team from entry-level associates to seasoned senior contributors, then this might be the gig for you.
WHAT WE VALUE
Collaboration: We believe the best work is done together.
Empathy: We believe in putting people first.
Quality: We believe in setting the standard for excellence.
Positive Impact: We believe in making the world a better place through our work.
* Shipping: We believe in creating things for the people using them.
Responsibilities
Design, build and deploy agentic solutions that leverage large language models to detect and prevent fraud, abuse, and security threats at scale — applying LLMs to problems such as content classification and multi-step agentic investigation.
Build well-engineered, production-grade systems that run reliably against high-volume event streams, making effective use of AI coding assistants to accelerate and improve your work.
Build and operate scalable ML systems on cloud platforms (such as Azure AI Foundry) for training, deploying, and serving models and agentic solutions in production.
Evaluate and improve existing models and agentic solutions using offline evaluations (including tool-use loops and LLM-as-judge evaluation), performance metrics, and feedback from operational deployments.
Identify vulnerabilities in products that lead to abuse, and provide consultation to product teams reviewing new features.
Collaborate closely with cross-functional teams including data scientists, software engineers, product managers and content moderators to integrate agentic solutions into production systems.
* Document the systems you help build and support the technical growth of your peers.
QUALIFICATIONS
Required Qualifications
* 4+ years experience in machine learning, or related field
+ OR Bachelor's Degree in Computer Science, Software Development, Electrical or Computer Engineering, Mathematical Sciences, or related field AND 2+ years experience in machine learning, or related field
+ OR Master's Degree in Machine Learning, Computer Science, Software Development, Electrical or Computer Engineering, Mathematical Sciences, or related field
+ OR equivalent experience.
Preferred Qualifications
Strong understanding of large language models — how they work — and hands-on experience applying them at scale, ideally for classification, agentic workflows, or agents.
Strong software engineering skills, including experience building with AI coding assistants.
Experience designing or evaluating agentic systems (tool-use loops, multi-step workflows, or LLM-as-judge evaluation).
Hands-on experience building and operating classification or detection systems at scale, including handling imbalanced data and precision/recall tradeoffs.
Experience in Trust and Safety, National Security or fighting spam, malware, fraud, and threat actor activity at scale.
Experience in responsible AI.
Experience in Safety-by-Design.
Experience with managing user data and privacy.
* Solid understanding of machine learning algorithms (supervised and unsupervised learning, anomaly detection, etc.) and their practical implementation.
COMPENSATION RANGE
The base salary range for this job is USD $107,700.00 - USD $285,900.00 /Yr.
These pay ranges are intended to cover roles based across the United States. An individual's base pay depends on various factors including geographical location and review of experience, knowledge, skills, abilities of the applicant. At GitHub certain roles are eligible for benefits and additional rewards, including annual bonus and stock. These rewards are allocated based on individual impact in role. In addition, certain roles also have the opportunity to earn sales incentives based on revenue or utilization, depending on the terms of the plan and the employee's role.
This position will be open for a minimum of 3 days, with applications accepted on an ongoing basis until the position is filled.
GITHUB LEADERSHIP PRINCIPLES
GitHub values
Customer-obsessed
Ship to learn
Growth mindset
Own the outcome
Better together
Diverse and inclusive
Manager fundamentals
Model
Coach
* Care
Leadership principles
Create clarity
Generate energy
* Deliver success
WHO WE ARE
GitHub is the world’s leading AI-powered developer platform with 150 million developers and counting. We’re also home to the biggest open-source community on earth (and 99% of the world’s software has open-source code in its DNA). Many of the apps and programs you use every day are built on GitHub.
Our teams are dreamers, doers, and pioneers, leading the way in AI, driving humanitarian efforts around the globe, and even sending open source to Mars (and beyond!). At GitHub, our goal is to create the space you need to do your best work. We’re remote-first and offer competitive pay, generous learning and growth opportunities, and excellent benefits to support you, wherever you are—because we know that people flourish when they can work on their own terms.
Join us, and let’s change the world, together.
EEO STATEMENT
GitHub is made up of people from a wide variety of backgrounds and lifestyles. We embrace diversity and invite applications from people of all walks of life. We don't discriminate against employees or applicants based on gender identity or expression, sexual orientation, race, religion, age, national origin, citizenship, disability, pregnancy status, veteran status, or any other differences. Also, if you have a disability, please let us know if there's any way we can make the interview process better for you; we're happy to accommodate!
See All 496+ Remote Senior ML Engineer Jobs
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Find JobsRemote Senior ML Engineer Job Market
Who's Hiring
- CVS Health34
- Alvarez & Marsal26
- Netflix20
- Liberty Mutual Insurance14
- Airbnb12
Top Industries Hiring
- Technology & Software145
- Consulting & Professional Services62
- Healthcare & Medical Services54
- Investment & Asset Management30
- Accounting & Auditing27
What Employers Look For
The qualifications that appear most often in remote senior ML engineer jobs.
- 5 or more years of hands-on machine learning engineering experience in production environments
- Proficiency in Python and ML frameworks such as PyTorch, TensorFlow, or JAX
- Experience designing and deploying end-to-end ML pipelines at scale
- Familiarity with MLOps tooling including experiment tracking, model registries, and CI/CD for models
- Strong understanding of distributed computing and cloud platforms such as AWS, GCP, or Azure
- Graduate degree in computer science, statistics, or a related quantitative field preferred
Tips for Your Remote Senior ML Engineer Job Search
Signal async fluency in your application materials
Remote hiring teams want proof you can collaborate without real-time back-and-forth. Show written design docs, RFC-style project write-ups, or documented experiment results in your portfolio so interviewers can evaluate your thinking before the first call.
Apply early to remote roles that fit
Migrate Mate lists remote senior ml engineer openings from across the U.S. in one place, so you can find roles that match your stack and seniority level and apply directly without sorting through on-site listings mixed in.
Highlight production ML ownership in your resume
Remote teams hire senior ml engineers to own model lifecycles independently. Call out specific systems you took from prototype to production, the MLOps tooling you used, and how you monitored and maintained models post-deployment, not just experiment accuracy.
Prepare for asynchronous technical screenings
Many remote-first companies send take-home ML case studies or ask you to review a model architecture and respond in writing. Practice explaining your reasoning in clear, structured prose, since written communication carries more weight in remote interviews than in on-site loops.
Target remote-first companies over remote-optional ones
Companies built around distributed teams offer senior ml engineers better async tooling, clearer documentation culture, and more equitable advancement than orgs where remote is an exception. Filter your search to roles explicitly listed as remote-first or fully distributed.
Remote Senior ML Engineer Jobs: Frequently Asked Questions
How do I get a remote senior ml engineer job?
Remote senior ml engineer roles go to candidates who can demonstrate self-direction, clear async written communication, and ownership of end-to-end ML systems without daily oversight. Remote-first companies and distributed teams screen heavily for experience shipping production models, familiarity with tools like MLflow, Weights and Biases, and cloud ML platforms, and the ability to unblock themselves. A strong GitHub portfolio with documented projects and evidence of cross-functional async collaboration gives you a clear edge.
Which companies hire remote senior ml engineers?
Remote senior ml engineer roles are posted by CVS Health, Alvarez & Marsal, and Netflix and others right now, based on current remote listings on Migrate Mate as of June 2026. These include remote-first tech companies, distributed fintech and healthtech teams, and AI-native startups that hire senior ml engineers entirely outside a central office.
Can you get a remote senior ml engineer job with no experience?
Yes, but remote entry into senior ml engineer roles is harder because remote teams expect independent execution from day one. Remote-first startups and AI product companies are the most open to candidates without formal experience if you can show production-quality personal or open-source ML projects, documented async workflows, and measurable results. A public portfolio with reproducible experiments and clear written documentation does more work than a degree or a prior job title.
Do you need a degree for remote senior ml engineer jobs?
Not always. Remote employers hiring senior ml engineers weigh demonstrated ability to build and deploy models over formal credentials, particularly at remote-first companies where output is the only visible signal. What opens doors is a strong portfolio of shipped ML work, fluency with current frameworks and MLOps tooling, and evidence that you can communicate technical decisions clearly in writing without a manager in the next seat.
Which industries hire the most remote senior ml engineers?
The sectors hiring the most remote senior ml engineers are Technology & Software, Consulting & Professional Services, and Healthcare & Medical Services, based on current remote listings on Migrate Mate as of June 2026. These industries rely on distributed engineering teams where senior ml engineers contribute across time zones without needing to be co-located with data infrastructure or product teams.
See All 496+ Remote Senior ML Engineer Jobs
Find roles that match your experience and apply in just a few clicks.
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