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Machine Learning Fellow Jobs (NOW HIRING)

Velo3D

Machine Learning Engineer

Fremont, CA

$150K - $220K/yr

We are seeking a Machine Learning Engineer to join our team developing machine learning solutions ... Working closely with process engineers, software engineers, and fellow ML engineers, you will ...

Velo3D

Machine Learning Engineer

Fremont, CA · On-site

$150K - $220K/yr

We are seeking a Machine Learning Engineer to join our team developing machine learning solutions ... Working closely with process engineers, software engineers, and fellow ML engineers, you will ...

Velo3D

Machine Learning Engineer

Fremont, CA

$150K - $220K/yr

We are seeking a Machine Learning Engineer to join our team developing machine learning solutions ... Working closely with process engineers, software engineers, and fellow ML engineers, you will ...

Velo3D

Machine Learning Engineer

Fremont, CA · On-site

$150K - $220K/yr

We are seeking a Machine Learning Engineer to join our team developing machine learning solutions ... Working closely with process engineers, software engineers, and fellow ML engineers, you will ...

Remark

Machine Learning Engineer

Boston, MA

Participate in frequent code-reviews with fellow team members. Qualifications * Strong background in Deep Learning, Machine Learning, and NLP. * Proficient in JavaScript and Python. * Expertise in ...

Arcadia Science

Platform Fellow

Emeryville, CA

$56K - $76K/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 ...

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Machine Learning Fellow information

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$25K

$59K

$83.5K

How much do machine learning fellow jobs pay per year?

As of Jun 20, 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 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.

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 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.
More about Machine Learning Fellow jobs
What job categories do people searching Machine Learning Fellow jobs look for? The top searched job categories for Machine Learning Fellow jobs are:
Machine Learning Fellow jobs near you
Infographic showing various Machine Learning Fellow job openings in the United States as of June 2026, with employment types broken down into 76% Full Time, 15% Part Time, 8% Contract, and 1% Nights. Highlights an 94% Physical, 1% Hybrid, and 5% Remote job distribution, with an average salary of $59,022 per year, or $28.4 per hour.
Postdoctoral Fellow in Geometric Machine Learning

Postdoctoral Fellow in Geometric Machine Learning

Harvard University

Cambridge, MA • On-site

$67K - $91K/yr

Full-time

Posted 5 days ago

Harvard University rating

8.1

Company rating: 8.1 out of 10

Based on 7 frontline employees who took The Breakroom Quiz

131st of 538 rated colleges and universities

Job description

Position
Details
Title
Postdoctoral Fellow in Geometric Machine Learning
School
Harvard John A. Paulson School of Engineering and Applied Sciences
Department/Area
Applied Math
Position Description
A postdoctoral position is available in the Geometric Machine Learning Group at Harvard University, led by Prof. Melanie Weber. This role offers an opportunity to perform research at the intersection of Geometry and Machine Learning, with a focus on studying geometric structures in data and models and how to leverage such structure for the design of efficient machine learning algorithms with provable guarantees. Research areas include Representation Learning, Machine learning and Optimization on graphs and manifolds, as well as applications of geometric methods in the Sciences.
This is a one-year position with the possibility of extension.
For more details on our research and recent publications, see the Geometric Machine Learning Group's website: https://weber.seas.harvard.edu
For questions, please email mweber@seas.harvard.edu .
Applications will be reviewed on a rolling basis.
Basic Qualifications
A Ph.D. in Mathematics, Computer Science, or a related field, by the start of the appointment.
Additional Qualifications
Special Instructions
To apply, please submit the following materials:
  1. CV
  2. Research Statement outlining your current and future research interests
  3. Three Reference Letters
  4. Copies of two publications representative of your work and research interest

SEAS is dedicated to building a diverse and welcoming community.
Contact Information
For more details on our research and recent publications, see the Geometric Machine Learning Group's website: https://weber.seas.harvard.edu
Contact Email
mweber@seas.harvard.edu
Salary Range
$67,600 - $91,826
Pay offered to the selected candidate is dependent on factors such as rank, years of experience, training or qualification, field of scholarship, and accomplishments in the field.
Minimum Number of References Required
3
Maximum Number of References Allowed
3
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