Remote Machine Learning Manager Jobs
Remote Machine Learning Manager jobs are open across technology, finance, and healthcare at remote-first companies and distributed teams, from senior individual-contributor-to-manager transitions to director-level ML leadership roles. Employers hiring remotely 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 Machine Learning Manager 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 Machine Learning Manager Jobs
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Find JobsRemote Machine Learning Manager 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 machine learning manager jobs.
- 5+ years of machine learning experience with at least 2 years managing or leading teams
- Proficiency in Python and frameworks such as PyTorch, TensorFlow, or JAX
- Experience taking machine learning models from prototype to production at scale
- Strong cross-functional collaboration skills with product, engineering, and data teams
- Familiarity with MLOps tooling including experiment tracking, model registries, and CI/CD pipelines
- Graduate degree in computer science, statistics, mathematics, or a closely related field
Tips for Your Remote Machine Learning Manager Job Search
Apply early to remote roles that fit
Migrate Mate lists remote machine learning manager openings from across the U.S. in one place, so you can find roles that match your background and apply directly without sorting through unrelated listings.
Prove async leadership before the interview
Remote employers want evidence you can manage distributed engineers without daily standups. Write up a concise decision log or architecture memo from a past project and share it during the process. Concrete written artifacts outperform verbal claims about remote readiness.
Build your remote ML management portfolio
Document the models you have shipped, the team structures you have run, and the outcomes you have delivered in a public or shareable format. Remote hiring managers review portfolios before calls because they cannot walk the floor and observe your work style in person.
Prepare for distributed-team interview formats
Remote machine learning manager interviews often include a written take-home case, an async video screen, and a panel call across multiple time zones. Practice narrating technical tradeoffs in writing and structuring your answers for asynchronous review, not just real-time delivery.
Signal self-direction clearly in your application
Remote machine learning manager roles attract candidates who default to independent problem-solving and proactive communication. Use your application materials to show specific instances where you drove an ML initiative from scoping through deployment with minimal direction from above.
Remote Machine Learning Manager Jobs: Frequently Asked Questions
How do I get a remote machine learning manager job?
Target remote-first technology companies, fintech firms, and healthcare AI teams, which hire machine learning managers without requiring on-site presence. Remote employers screen heavily for written communication, comfort with async collaboration tools like Slack and Notion, and the ability to drive ML roadmaps without daily in-person oversight. Candidates who document prior remote or cross-functional leadership, even informally, stand out over those who only list technical credentials.
Which companies hire remote machine learning managers?
Companies hiring remote machine learning managers right now include CVS Health, Alvarez & Marsal, and Netflix, based on current remote listings on Migrate Mate as of June 2026. Remote-first technology firms, distributed fintech platforms, and enterprise software companies with global data teams tend to hire machine learning managers fully remotely.
Can you get a remote machine learning manager job with no experience?
Yes, but remote entry-level machine learning manager roles are rare because employers expect you to lead distributed engineers with minimal supervision from day one. The clearest path in is through remote ML engineer roles at smaller companies where you naturally absorb team leadership, then parlay that into a formal manager title. Demonstrating async mentorship, written technical decision-making, and ownership of shipped models can substitute for a traditional management title.
Do you need a degree for remote machine learning manager jobs?
Not always. Most remote employers list a degree in computer science, statistics, or a related field as preferred rather than required, especially when a candidate brings demonstrable results. Remote hiring teams weigh production ML systems you have shipped, open-source contributions, and evidence you can lead engineers across time zones as heavily as formal credentials.
Which industries hire the most remote machine learning managers?
The sectors hiring the most remote machine learning managers are Technology & Software, Consulting & Professional Services, and Healthcare & Medical Services, based on current remote listings on Migrate Mate as of June 2026. These sectors concentrate remote ML leadership because their engineering and data teams are already distributed across multiple locations and time zones.
See All 496+ Remote Machine Learning Manager Jobs
Find roles that match your experience and apply in just a few clicks.
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