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 Atlassian, Whatnot, and Amgen. Find a role that fits below and apply directly.
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Showing 5 of 184+ Remote Machine Learning Manager jobs
Join Amgen’s Mission of Serving Patients
At Amgen, if you feel like you’re part of something bigger, it’s because you are. Our shared mission—to serve patients living with serious illnesses—drives all that we do.
Since 1980, we’ve helped pioneer the world of biotech in our fight against the world’s toughest diseases. With our focus on four therapeutic areas –Oncology, Inflammation, General Medicine, and Rare Disease– we reach millions of patients each year. Amgen is advancing a broad and deep pipeline of medicines to treat cancer, heart disease, inflammatory conditions, rare diseases, and obesity and obesity-related conditions. As a member of the Amgen team, you’ll help make a lasting impact on the lives of patients as we research, manufacture, and deliver innovative medicines to help people live longer, fuller happier lives.
Our award-winning culture is collaborative, innovative, and science based. If you have a passion for challenges and the opportunities that lay within them, you’ll thrive as part of the Amgen team. Join us and transform the lives of patients while transforming your career.
Principal Machine Learning Engineer
What you will do
Let’s do this. Let’s change the world. In this vital role you will Own enterprise AI/ML architecture, standards, APIs, and guardrails across cloud/on-prem.
We are seeking a Principal Machine Learning Engineer—Amgen’s most senior individual-contributor authority on building and scaling end-to-end machine-learning and generative-AI solutions. Sitting at the intersection of engineering excellence and data-science enablement, you will develop, deploy and monitor models—classical ML, deep learning and LLMs—securely and cost-effectively. Acting as a “player-coach,” you will establish AI solution strategy, define technical standards, and partner with DevOps, Security, Compliance and Product teams to deliver a frictionless, enterprise-grade AI solutions.
Roles & Responsibilities:
- Own enterprise AI/ML architecture, standards, APIs, and guardrails across cloud/on-prem.
- Build production ML/GenAI solutions and lightweight apps delivering sub-second insights.
- Build end-to-end ML pipelines—data ingestion, feature engineering, training, hyper-parameter optimisation, evaluation, registration and automated promotion—using Kubeflow, SageMaker Pipelines, Open AI SDK or equivalent MLOps stacks.
- Build and maintain full-stack AI applications by integrating model services with lightweight UI components, workflow engines or business-logic layers so insights reach users with sub-second latency.
- Establish observability, SLOs, and safe deploys (blue-green/canary, shadow, rollbacks) with incident runbooks.
- Lead rigorous evaluation (offline/online, A/B), drift detection, and automated retraining.
- Architect LLM/RAG with prompt management, safety guardrails, and optimized inference.
- Enforce data quality, lineage, and model/data cards; apply privacy-preserving techniques where needed.
- Contribute reusable ML/GenAI components—feature stores, model registries, experiment-tracking libraries—and evangelize best practices that raise engineering velocity across squads.
- Perform exploratory data analysis and feature ideation on complex, high-dimensional datasets to inform algorithm selection and ensure model robustness.
- Prototype and benchmark new algorithms, offering guidance on scalability trade-offs and production-readiness while co-owning model-performance KPIs.
- Translate domain needs (R&D, Manufacturing, Commercial) into roadmaps; mentor teams and communicate trade-offs.
What we expect of you
We are all different, yet we all use our unique contributions to serve patients. The professional we seek is a Principal Machine Learning Engineer with these qualifications.
Basic Qualifications:
Doctorate degree and 2 years of Machine Learning Engineer experience
OR
Master’s degree and 6 years of Machine Learning Engineer experience
OR
Bachelor’s degree and 8 years of Machine Learning Engineer experience
OR
Associate’s degree and 10 years of Machine Learning Engineer experience
OR
High school diploma / GED and 12 years of Machine Learning Engineer experience
In addition to meeting at least one of the above requirements, you must have a minimum of 2 years experience directly managing people and/or leadership experience leading teams, projects, programs, or directing the allocation or resources. Your managerial experience may run concurrently with the required technical experience referenced above
- 3-5 years in AI/ML and enterprise software.
- Strong command of machine-learning algorithms—regression, tree-based ensembles, clustering, dimensionality reduction, time-series models, deep-learning architectures (CNNs, RNNs, transformers) and modern LLM/RAG techniques—with the judgment to choose, tune and operationalize the right method for a given business problem.
- Proven track record selecting and integrating AI SaaS/PaaS offerings and building custom ML services at scale.
- Expert knowledge of GenAI tooling: vector databases, RAG pipelines, prompt-engineering DSLs and agent frameworks (e.g., LangChain, LangGraph, Semantic Kernel).
- Proficiency in Python and Java; containerization (Docker/K8s); cloud (AWS, Azure or GCP) and modern DevOps/MLOps (GitHub Actions, Bedrock/SageMaker Pipelines).
- Strong business-case skills—able to model TCO vs. NPV and present trade-offs to executives.
- Exceptional stakeholder management; can translate complex technical concepts into concise, outcome-oriented narratives.
Preferred Qualifications:
- Experience in Biotechnology or pharma industry is a big plus
- Published thought-leadership or conference talks on enterprise GenAI adoption.
- Master’s degree in Computer Science and or Data Science
- Familiarity with Agile methodologies and Scaled Agile Framework (SAFe) for project delivery.
Education and Professional Certifications
- Master’s degree with 10-12 + years of experience in Computer Science, IT or related field
OR
- Bachelor’s degree with 12-14 + years of experience in Computer Science, IT or related field
- Certifications on GenAI/ML platforms (AWS AI, Azure AI Engineer, Google Cloud ML, etc.) are a plus.
Soft Skills:
- Excellent analytical and troubleshooting skills.
- Strong verbal and written communication skills
- Ability to work effectively with global, virtual teams
- High degree of initiative and self-motivation.
- Ability to manage multiple priorities successfully.
- Team-oriented, with a focus on achieving team goals.
- Ability to learn quickly, be organized and detail oriented.
- Strong presentation and public speaking skills.
What you can expect of us
As we work to develop treatments that take care of others, we also work to care for your professional and personal growth and well-being. From our competitive benefits to our collaborative culture, we’ll support your journey every step of the way.
The expected annual salary range for this role in the U.S. (excluding Puerto Rico) is posted. Actual salary will vary based on several factors including but not limited to, relevant skills, experience, and qualifications.
In addition to the base salary, Amgen offers a Total Rewards Plan, based on eligibility, comprising of health and welfare plans for staff and eligible dependents, financial plans with opportunities to save towards retirement or other goals, work/life balance, and career development opportunities that may include:
- A comprehensive employee benefits package, including a Retirement and Savings Plan with generous company contributions, group medical, dental and vision coverage, life and disability insurance, and flexible spending accounts
- A discretionary annual bonus program, or for field sales representatives, a sales-based incentive plan
- Stock-based long-term incentives
- Award-winning time-off plans
- Flexible work models where possible. Refer to the Work Location Type in the job posting to see if this applies.
and make a lasting impact with the Amgen team.
careers.amgen.com
In any materials you submit, you may redact or remove age-identifying information such as age, date of birth, or dates of school attendance or graduation. You will not be penalized for redacting or removing this information.
Application deadline
Amgen does not have an application deadline for this position; we will continue accepting applications until we receive a sufficient number or select a candidate for the position.
Sponsorship
Sponsorship for this role is not guaranteed.
As an organization dedicated to improving the quality of life for people around the world, Amgen fosters an inclusive environment of diverse, ethical, committed and highly accomplished people who respect each other and live the Amgen values to continue advancing science to serve patients. Together, we compete in the fight against serious disease.
Amgen is an Equal Opportunity employer and will consider all qualified applicants for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, protected veteran status, disability status, or any other basis protected by applicable law.
We will ensure that individuals with disabilities are provided reasonable accommodation 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.
Join Amgen’s Mission of Serving Patients
At Amgen, if you feel like you’re part of something bigger, it’s because you are. Our shared mission—to serve patients living with serious illnesses—drives all that we do.
Since 1980, we’ve helped pioneer the world of biotech in our fight against the world’s toughest diseases. With our focus on four therapeutic areas –Oncology, Inflammation, General Medicine, and Rare Disease– we reach millions of patients each year. Amgen is advancing a broad and deep pipeline of medicines to treat cancer, heart disease, inflammatory conditions, rare diseases, and obesity and obesity-related conditions. As a member of the Amgen team, you’ll help make a lasting impact on the lives of patients as we research, manufacture, and deliver innovative medicines to help people live longer, fuller happier lives.
Our award-winning culture is collaborative, innovative, and science based. If you have a passion for challenges and the opportunities that lay within them, you’ll thrive as part of the Amgen team. Join us and transform the lives of patients while transforming your career.
Principal Machine Learning Engineer
What you will do
Let’s do this. Let’s change the world. In this vital role you will Own enterprise AI/ML architecture, standards, APIs, and guardrails across cloud/on-prem.
We are seeking a Principal Machine Learning Engineer—Amgen’s most senior individual-contributor authority on building and scaling end-to-end machine-learning and generative-AI solutions. Sitting at the intersection of engineering excellence and data-science enablement, you will develop, deploy and monitor models—classical ML, deep learning and LLMs—securely and cost-effectively. Acting as a “player-coach,” you will establish AI solution strategy, define technical standards, and partner with DevOps, Security, Compliance and Product teams to deliver a frictionless, enterprise-grade AI solutions.
Roles & Responsibilities:
- Own enterprise AI/ML architecture, standards, APIs, and guardrails across cloud/on-prem.
- Build production ML/GenAI solutions and lightweight apps delivering sub-second insights.
- Build end-to-end ML pipelines—data ingestion, feature engineering, training, hyper-parameter optimisation, evaluation, registration and automated promotion—using Kubeflow, SageMaker Pipelines, Open AI SDK or equivalent MLOps stacks.
- Build and maintain full-stack AI applications by integrating model services with lightweight UI components, workflow engines or business-logic layers so insights reach users with sub-second latency.
- Establish observability, SLOs, and safe deploys (blue-green/canary, shadow, rollbacks) with incident runbooks.
- Lead rigorous evaluation (offline/online, A/B), drift detection, and automated retraining.
- Architect LLM/RAG with prompt management, safety guardrails, and optimized inference.
- Enforce data quality, lineage, and model/data cards; apply privacy-preserving techniques where needed.
- Contribute reusable ML/GenAI components—feature stores, model registries, experiment-tracking libraries—and evangelize best practices that raise engineering velocity across squads.
- Perform exploratory data analysis and feature ideation on complex, high-dimensional datasets to inform algorithm selection and ensure model robustness.
- Prototype and benchmark new algorithms, offering guidance on scalability trade-offs and production-readiness while co-owning model-performance KPIs.
- Translate domain needs (R&D, Manufacturing, Commercial) into roadmaps; mentor teams and communicate trade-offs.
What we expect of you
We are all different, yet we all use our unique contributions to serve patients. The professional we seek is a Principal Machine Learning Engineer with these qualifications.
Basic Qualifications:
Doctorate degree and 2 years of Machine Learning Engineer experience
OR
Master’s degree and 6 years of Machine Learning Engineer experience
OR
Bachelor’s degree and 8 years of Machine Learning Engineer experience
OR
Associate’s degree and 10 years of Machine Learning Engineer experience
OR
High school diploma / GED and 12 years of Machine Learning Engineer experience
In addition to meeting at least one of the above requirements, you must have a minimum of 2 years experience directly managing people and/or leadership experience leading teams, projects, programs, or directing the allocation or resources. Your managerial experience may run concurrently with the required technical experience referenced above
- 3-5 years in AI/ML and enterprise software.
- Strong command of machine-learning algorithms—regression, tree-based ensembles, clustering, dimensionality reduction, time-series models, deep-learning architectures (CNNs, RNNs, transformers) and modern LLM/RAG techniques—with the judgment to choose, tune and operationalize the right method for a given business problem.
- Proven track record selecting and integrating AI SaaS/PaaS offerings and building custom ML services at scale.
- Expert knowledge of GenAI tooling: vector databases, RAG pipelines, prompt-engineering DSLs and agent frameworks (e.g., LangChain, LangGraph, Semantic Kernel).
- Proficiency in Python and Java; containerization (Docker/K8s); cloud (AWS, Azure or GCP) and modern DevOps/MLOps (GitHub Actions, Bedrock/SageMaker Pipelines).
- Strong business-case skills—able to model TCO vs. NPV and present trade-offs to executives.
- Exceptional stakeholder management; can translate complex technical concepts into concise, outcome-oriented narratives.
Preferred Qualifications:
- Experience in Biotechnology or pharma industry is a big plus
- Published thought-leadership or conference talks on enterprise GenAI adoption.
- Master’s degree in Computer Science and or Data Science
- Familiarity with Agile methodologies and Scaled Agile Framework (SAFe) for project delivery.
Education and Professional Certifications
- Master’s degree with 10-12 + years of experience in Computer Science, IT or related field
OR
- Bachelor’s degree with 12-14 + years of experience in Computer Science, IT or related field
- Certifications on GenAI/ML platforms (AWS AI, Azure AI Engineer, Google Cloud ML, etc.) are a plus.
Soft Skills:
- Excellent analytical and troubleshooting skills.
- Strong verbal and written communication skills
- Ability to work effectively with global, virtual teams
- High degree of initiative and self-motivation.
- Ability to manage multiple priorities successfully.
- Team-oriented, with a focus on achieving team goals.
- Ability to learn quickly, be organized and detail oriented.
- Strong presentation and public speaking skills.
What you can expect of us
As we work to develop treatments that take care of others, we also work to care for your professional and personal growth and well-being. From our competitive benefits to our collaborative culture, we’ll support your journey every step of the way.
The expected annual salary range for this role in the U.S. (excluding Puerto Rico) is posted. Actual salary will vary based on several factors including but not limited to, relevant skills, experience, and qualifications.
In addition to the base salary, Amgen offers a Total Rewards Plan, based on eligibility, comprising of health and welfare plans for staff and eligible dependents, financial plans with opportunities to save towards retirement or other goals, work/life balance, and career development opportunities that may include:
- A comprehensive employee benefits package, including a Retirement and Savings Plan with generous company contributions, group medical, dental and vision coverage, life and disability insurance, and flexible spending accounts
- A discretionary annual bonus program, or for field sales representatives, a sales-based incentive plan
- Stock-based long-term incentives
- Award-winning time-off plans
- Flexible work models where possible. Refer to the Work Location Type in the job posting to see if this applies.
and make a lasting impact with the Amgen team.
careers.amgen.com
In any materials you submit, you may redact or remove age-identifying information such as age, date of birth, or dates of school attendance or graduation. You will not be penalized for redacting or removing this information.
Application deadline
Amgen does not have an application deadline for this position; we will continue accepting applications until we receive a sufficient number or select a candidate for the position.
Sponsorship
Sponsorship for this role is not guaranteed.
As an organization dedicated to improving the quality of life for people around the world, Amgen fosters an inclusive environment of diverse, ethical, committed and highly accomplished people who respect each other and live the Amgen values to continue advancing science to serve patients. Together, we compete in the fight against serious disease.
Amgen is an Equal Opportunity employer and will consider all qualified applicants for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, protected veteran status, disability status, or any other basis protected by applicable law.
We will ensure that individuals with disabilities are provided reasonable accommodation 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.
See All 184+ Remote Machine Learning Manager Jobs
Find roles that match your experience and apply in just a few clicks.
Find JobsRemote Machine Learning Manager Job Market
Who's Hiring
- Atlassian13
- Whatnot7
- Amgen5
- Airbnb5
- Lockheed Martin5
Top Industries Hiring
- Technology & Software26
- Hospitality & Tourism6
- Consulting & Professional Services5
- Banking & Financial Services3
- Retail2
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.
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 Atlassian, Whatnot, and Amgen, based on current remote listings on Migrate Mate as of September 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, Hospitality & Tourism, and Consulting & Professional Services, based on current remote listings on Migrate Mate as of September 2026. These sectors concentrate remote ML leadership because their engineering and data teams are already distributed across multiple locations and time zones.
See All 184+ Remote Machine Learning Manager Jobs
Find roles that match your experience and apply in just a few clicks.
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