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Machine Learning Fellow Jobs (NOW HIRING)

Platform Fellow

Emeryville, CA

$56.70K - $76.90K/yr

We are seeking a Platform Fellow to join our Platform team for a 3-month fellowship. Platform uses ... PhD in computational biology, statistics, machine learning, genetics, evolutionary biology, or a ...

Senior Machine Learning Engineer

Pittsburgh, PA · On-site

$118.90K - $156.80K/yr

... edge machine learning technology that automates complex processes, enabling end-users to make ... fellow taxonomists, software engineers, data scientists, data engineers, and QA engineers ...

You'll work closely with AI model developers, fellow machine learning engineers, and our platform engineering team. You'll ensure that Artera's model developers can rely on highly efficient, large ...

You'll work closely with AI model developers, fellow machine learning engineers, and our platform engineering team. You'll ensure that Artera's model developers can rely on highly efficient, large ...

Post-Doctoral Fellow

Aurora, CO

$49.80K - $67.60K/yr

Postdoctoral Fellow Position #00848430: - Requisition #:39971 Job Summary: The Pividori Lab (pivlab ... Dr. Milton Pividori) designs and implements machine-learning methods that are applied to human ...

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Showing results 1-20

Machine Learning Fellow information

See salary details

$25K

$59K

$83.5K

How much do machine learning fellow jobs pay per year?

As of May 29, 2026, the average yearly pay for machine learning fellow in the United States is $59,022.00, according to ZipRecruiter salary data. Most workers in this role earn between $49,000.00 and $66,500.00 per year, depending on experience, location, and employer.

What are the key skills and qualifications needed to thrive as a Machine Learning Fellow, and why are they important?

A Machine Learning Fellow typically needs a strong background in mathematics, statistics, and programming (Python, R, or similar), often supported by an advanced degree in computer science, data science, or related fields. Familiarity with machine learning frameworks (such as TensorFlow or PyTorch), cloud platforms, and data analysis tools is essential. Critical thinking, curiosity, and effective communication help fellows solve complex problems and share findings with technical and non-technical audiences. These skills enable effective model development, impactful research, and successful collaboration in interdisciplinary teams.

What are some typical projects or tasks a Machine Learning Fellow can expect to work on during their fellowship?

As a Machine Learning Fellow, you can expect to engage in hands-on projects such as developing and optimizing machine learning models, analyzing large datasets, and collaborating with research scientists or engineers. Fellows often participate in exploratory research, contribute to publications, or assist with deploying models into production environments. The role typically involves regular team meetings, code reviews, and opportunities to present your findings to both technical and non-technical audiences, offering valuable experience for future career advancement.

What is a Machine Learning Fellow?

A Machine Learning Fellow is typically an early-career or advanced student involved in a structured fellowship program focused on machine learning research or applications. These fellowships provide opportunities to work on real-world projects, collaborate with experts, and deepen knowledge in areas such as data analysis, model development, and artificial intelligence. Fellows often contribute to research papers, attend workshops, and gain hands-on experience with cutting-edge technologies, preparing them for future roles in academia or industry.

What is the difference between Machine Learning Fellow vs Data Scientist?

AspectMachine Learning FellowData Scientist
Required CredentialsAdvanced degree in CS, ML, or related field; research experienceDegree in CS, statistics, or related; some roles prefer experience in analytics
Work EnvironmentResearch-focused, academic or corporate R&D teamsBusiness analytics, product development, or consulting teams
Employer & Industry UsageUniversities, research labs, tech companiesTech firms, finance, healthcare, e-commerce
Search & Comparison IntentFocus on research, advanced ML projectsData analysis, insights, and modeling

While both roles involve working with data and machine learning, a Machine Learning Fellow typically focuses on research and developing new algorithms, often in academic or R&D settings. Data Scientists apply ML techniques to solve business problems, analyze data, and generate insights. The roles overlap in skills and tools but differ mainly in their primary focus and work environment.

More about Machine Learning Fellow jobs
Infographic showing various Machine Learning Fellow job openings in the United States as of May 2026, with employment types broken down into 100% Full Time. Highlights an 100% In-person job distribution, with an average salary of $59,022 per year, or $28.4 per hour.
Machine Learning Fellow - Human Frontier Collective (US)

Machine Learning Fellow - Human Frontier Collective (US)

Scale AI, Inc.

San Francisco, CA • On-site, Remote

Other

Posted 28 days ago


Job description

PLEASE NOTE:This is a fully remote, 1099 independent contractor opportunity with an estimated duration of six months and the potential for extension. To be eligible, candidates must be authorized to work in the United States; visa sponsorship is not available for this role.

About the Program

The Human Frontier Collective (HFC) Fellowship brings together top researchers and domain experts to collaborate on high-impact work that are shaping the future of AI. As an HFC Fellow, you'll apply your academic and professional expertise to help design, evaluate, and interpret advanced generative AI systems-while gaining exposure to cutting-edge research and working alongside an interdisciplinary network of leading thinkers.

What You'll Do
  • ML Projects: Get invited to engage in high-impact projects with our partnered AI labs and platforms. Help models understand real-world deep learning workflows by designing, reviewing, and optimizing PyTorch models, evaluating complex ML code and AI-generated implementations for efficiency and correctness, and advising on GPU optimization, scaling, and trade-offs.
  • HFC Community: Beyond the work, you'll become part of a supportive, interdisciplinary network of innovators and thought leaders committed to advancing frontier AI across domains.
  • Contribute to Research Publications: Collaborate with Scale's research team to co-author technical reports and research papers-boosting your academic visibility and professional recognition(e.g., SciPredict, PropensityBench, Professional Reasoning Benchmark).
Who Should Apply
  • Education:PhD or postdoctoral degree in Computer Science, Computer Engineering, or a related field.
  • Professional Background:1-3+ years of experience as a Machine Learning Engineer or Data Scientist.
  • Skills: Strong proficiency in Python and modern ML frameworks (PyTorch, TensorFlow).Experience with cloud infrastructure (AWS) and MLOps tools (Docker, Langchain) is a plus.
  • Professional Mindset: Detail-oriented, innovative thinker with a passion in applied AI research and a commitment to collaboration.
Why Join the HFC?
  • Professional Development: High-impact experts expand their influence through review projects, advisory roles, and research, while deepening their AI expertise, strengthening analytical and problem-solving skills, and engaging with pioneering AI applications in science and technology.
  • Join a Top-Tier Network: Collaborate with a global network of engineers and experts to advance responsible AI through impactful, flexible research and training. 80% of our members come from leading institutions.
  • Flexible Schedule: Set your own schedule, with flexible 10-40 hour weeks that fit around your life and other commitments.
  • Competitive Pay: Project pay rates vary across platforms and are depending on a number of factors, including but not limited to; projects, scope, skillset, and location.
Application Process
  1. Apply: We review applications on a rolling basis.
  2. Interview: Candidates will get to discuss their research experience, professional background, and alignment with our mission to advance human-centered AI.
  3. Join the Collective: Successful candidates will receive an invitation to join the Human Frontier Collective Fellowship.

PLEASE NOTE:Our policy requires a 90-day waiting period before reconsidering candidates for the same role. This allows us to ensure a fair and thorough evaluation of all applicants.

About Us:

At Scale, our mission is to develop reliable AI systems for the world's most important decisions. Our products provide the high-quality data and full-stack technologies that power the world's leading models, and help enterprises and governments build, deploy, and oversee AI applications that deliver real impact. We work closely with industry leaders like Meta, Ernst & Young, Mayo Clinic, Time Inc., the Government of Qatar, and U.S. government agencies including the Army and Air Force. We are expanding our team to accelerate the development of AI applications.

We believe that everyone should be able to bring their whole selves to work, which is why we are proud to be an inclusive and equal opportunity workplace. We are committed to equal employment opportunity regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability status, gender identity or Veteran status.

We are committed to working with and providing reasonable accommodations to applicants with physical and mental disabilities. If you need assistance and/or a reasonable accommodation in the application or recruiting process due to a disability, please contact us at accommodations@scale.com. Please see the United States Department of Labor's Know Your Rights poster for additional information.

We comply with the United States Department of Labor's Pay Transparency provision.

PLEASE NOTE: We collect, retain and use personal data for our professional business purposes, including notifying you of job opportunities that may be of interest and sharing with our affiliates. We limit the personal data we collect to that which we believe is appropriate and necessary to manage applicants' needs, provide our services, and comply with applicable laws. Any information we collect in connection with your application will be treated in accordance with our internal policies and programs designed to protect personal data. Please see our privacy policy for additional information.