Remote Machine Learning Intern Jobs
Remote Machine Learning Intern jobs are actively hiring across the U.S., with remote-first firms and distributed teams in tech, finance, and healthcare bringing on interns who can contribute from anywhere. Employers hiring remotely right now include Atlassian, Whatnot, and Amgen. See the openings below and apply to the ones that match your experience.
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Showing 5 of 184+ Remote Machine Learning Intern 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 Intern Jobs
Find roles that match your experience and apply in just a few clicks.
Find JobsRemote Machine Learning Intern 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 intern jobs.
- Proficiency in Python and at least one ML framework such as PyTorch or TensorFlow
- Hands-on experience with data preprocessing, feature engineering, and model evaluation
- Familiarity with machine learning concepts including supervised, unsupervised, and deep learning
- Currently enrolled in or recently completed a bachelor's or master's degree in computer science, data science, or a related field
- Experience with data manipulation libraries such as NumPy, pandas, or scikit-learn
- Demonstrated project work or research published in a portfolio, GitHub repository, or academic paper
Tips for Your Remote Machine Learning Intern Job Search
Show async work habits in your portfolio
Remote machine learning intern employers want proof you can work without daily check-ins. Include a README on every GitHub project explaining your reasoning, decisions, and results as if a remote teammate needs to understand your work without asking you questions.
Apply early to remote roles that fit
Migrate Mate lists remote machine learning intern openings from companies hiring across the U.S. in one place, so you can find roles that match your skills and apply directly without sorting through mixed in-office listings.
Signal remote readiness with your tools
Call out the remote-native tools you already use in your resume skills section: Jupyter notebooks on cloud platforms like Google Colab or AWS SageMaker, version control with Git, and experiment tracking with tools like MLflow show remote teams you can plug into their existing workflow immediately.
Prepare for async-first remote interviews
Remote machine learning intern interviews often include a take-home coding or modeling assignment before any live call. Practice explaining your model choices in writing as clearly as you would in a video presentation, since hiring managers at distributed teams frequently evaluate written technical reasoning as much as your code output.
Remote Machine Learning Intern Jobs: Frequently Asked Questions
How do I get a remote machine learning intern job?
Target companies that already run distributed engineering or data science teams, since they have workflows built for remote interns. Remote employers screen for self-direction, clear async written communication, and hands-on skills like Python, TensorFlow, or PyTorch demonstrated through GitHub projects or Kaggle notebooks. A portfolio showing you can scope a problem, build a model, and document results independently gives you a clear edge over candidates without one.
Which companies hire remote machine learning interns?
Remote machine learning intern roles are posted by Atlassian, Whatnot, and Amgen and others right now, based on current remote listings on Migrate Mate as of September 2026. Remote-first tech firms, AI-native startups, and distributed data teams in software, fintech, and healthcare are among the most active hirers for this role.
Can you get a remote machine learning intern job with no experience?
Yes, but remote entry roles are harder to land because employers expect you to work independently from day one without in-office supervision. To stand out without prior job experience, build a public project portfolio on GitHub, complete structured ML courses with verifiable certificates, and contribute to open-source repositories. Smaller remote-first startups and research labs tend to be more open to strong self-taught candidates than large enterprise distributed teams.
Do you need a degree for remote machine learning intern jobs?
Not always. Many remote employers weigh demonstrated skills over formal credentials for intern-level machine learning roles, particularly at startups and AI-focused product companies. What matters most is evidence you can build and evaluate models: a strong GitHub portfolio, completed Kaggle competitions, or coursework in statistics and linear algebra carry real weight when a degree is still in progress or absent.
Which industries hire the most remote machine learning interns?
The sectors hiring the most remote machine learning interns are Technology & Software, Hospitality & Tourism, and Consulting & Professional Services, based on current remote listings on Migrate Mate as of September 2026. These industries favor distributed teams because their data pipelines, model development, and code review workflows translate well to fully remote collaboration.
See All 184+ Remote Machine Learning Intern Jobs
Find roles that match your experience and apply in just a few clicks.
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