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Machine Learning Fellow Jobs (NOW HIRING)

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 ...

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Machine Learning Fellow information

See salary details

$25K

$59K

$83.5K

How much do machine learning fellow jobs pay per year?

As of Jul 12, 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 July 2026, with employment types broken down into 75% Full Time, 23% Part Time, 1% Temporary, and 1% Contract. Highlights an 91% Physical, and 9% Remote job distribution, with an average salary of $59,022 per year, or $28.4 per hour.

Machine Learning Fellowship (6-12 months)

Volkswagen AG

Belmont, CA • On-site

Other

Posted 3 days ago

New

Job description

Brief Role Description

At the Innovation & Engineering Center California (IECC), we represent the Volkswagen Group in applied research and development. Located in the heart of Silicon Valley, we create bold new ideas for the Volkswagen, Audi, Bentley, Lamborghini, Bugatti and Porsche brands. We're a team of engineers, designers, scientists, and psychologists looking to develop innovations for future generations of cars, and to transfer technologies from many industries and research institutions into the automotive domain. Our mission is to drive change which means we are not only impacting one of the world's largest car makers, but also the lives of millions of people. Are you ready to join us?

*Six Month Minimum commitment  - Masters or PhD candidates only.
We are unable to consider International Students/OPT or CPT at this time.

Machine Learning Fellowship

Role Summary:

The perception and machine learning team is tasked to apply machine learning to the automotive industry. Applications include autonomous driving, manufacturing, material design, etc. The team develops state of the art AI solutions to solve complex and challenging problems by leveraging the latest techniques in machine learning on large data sets. At ICC, you will be involved in developing modern methods in the field of sensor data processing to enable safe and robust automated driving in any scenario. During this fellowship, you will be supporting a team of AI researchers and engineers to find suitable learning methods for robust perception.

Role Responsibilities

Role Responsibilities

  • Driving data pre-processing including checking labels, formatting, etc.
  • Support project team in building data pipelines for training deep neural networks.
  • Benchmarking and reporting of various neural network models performance.
  • Research into suitable new network architectures to for time series prediction, and anomalies detection.
  • Research into suitable new network architectures to improve the perception of the environment with a focus on optical sensors.
  • Research on supervised and unsupervised learning methods to estimate road participants' depth, motion, and velocity. 
  • Research on various neural networks for the interpretation of camera images (object detection, panoptic segmentation) and trajectory/motion planning.
  • Fusion of different neural networks to use shared resources to decrease memory and computation footprint.
Qualification requirements
  • Must be enrolled at a University/College or Graduation date must be within the last six months in a Masters or PhD program.
  • Must have a cumulative GPA of at least 3.0.
  • Strong Python programming skills.
  • Good experience using Linux.
  • Experience with deep learning frameworks such as TensorFlow and PyTorch.
  • Good knowledge of image processing and machine learning.
  • Independent work, initiative, motivation, ability to work in a team.
Competencies
Act as an owner
Be a pioneer
Excite customer
Handle complexity
Live integrity & compliance
Live passion
Perform together
Think ahead

Apply