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Research Assistant Machine Learning Jobs in Berkeley, CA

Gotion, Inc.

Machine Learning Engineer

Fremont, CA · On-site

You will collaborate closely with cross-disciplinary R&D teams to develop and deploy machine ... Design and implement novel machine learning and deep learning models tailored to internal research ...

Articul8

Machine Learning Engineer

Dublin, CA · On-site

$90 - $130/hr

You will work closely with other researchers and engineers to empower our next generation of domain ... Experience in machine learning projects in text or vision, e.g., has trained machine learning ...

Articul8

Machine Learning Engineer

Dublin, CA · On-site

You will work closely with other researchers and engineers to empower our next generation of domain ... Experience in machine learning projects in text or vision, e.g., has trained machine learning ...

PhysicsX

Machine Learning Engineer

San Francisco, CA · On-site

  • Medical

  • Retirement

  • PTO

With at least 2 years industry experience (post Masters or PhD) in a commercial, non-research ... This Role As a Machine Learning Engineer, you'll work closely with our Data Scientists, Simulation ...

Human Archive

Machine Learning Engineer

San Francisco, CA · On-site

$100K - $150K/yr

Research into human physical intelligence - including the human hand, proprioception, and vision ... The Opportunity As a Machine Learning Engineer, you'll work on multimodal perception, VLA training ...

PhysicsX

Machine Learning Engineer

San Francisco, CA · On-site +1

  • Medical

  • Retirement

  • PTO

With at least 2 years industry experience (post Masters or PhD) in a commercial, non-research ... This Role As a Machine Learning Engineer, you'll work closely with our Data Scientists, Simulation ...

Jobzhr

Machine Learning Engineer, Drive

San Francisco, CA · On-site

$204 - $299/hr

  • Medical

  • Dental

  • Vision

  • Life

  • Retirement

  • PTO

Optimization / Operations Research * Large Language Models (LLMs) or Vision-Language Models (VLMs) * Experience applying machine learning to estimation, ranking, prediction, optimization, or decision ...

New

DoorDash

Machine Learning Engineer, Drive

San Francisco, CA · On-site

  • Medical

  • Dental

  • Vision

  • Life

  • Retirement

  • PTO

Optimization / Operations Research * Large Language Models (LLMs) or Vision-Language Models (VLMs) * Experience applying machine learning to estimation, ranking, prediction, optimization, or decision ...

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All JobsResearch Machine Learning JobsResearch Assistant Machine Learning JobsResearch Assistant Machine Learning Jobs in Berkeley, CA

Research Assistant Machine Learning information

See Berkeley, CA salary details

$10

$26

$38

How much do research assistant machine learning jobs pay per hour?

As of Aug 14, 2026, the average hourly pay for research assistant machine learning in Berkeley, CA is $26.83, according to ZipRecruiter salary data. Most workers in this role earn between $22.64 and $31.20 per hour, depending on experience, location, and employer.

What is a research assistant machine learning?

A Research Assistant in Machine Learning supports research projects by implementing algorithms, analyzing data, and conducting experiments to advance AI models. They assist senior researchers by preprocessing datasets, developing machine learning models, and evaluating their performance. Responsibilities may also include coding, literature reviews, and writing research papers. This role is typically found in academia, research labs, or industry R&D teams. Strong programming skills, statistical knowledge, and familiarity with ML frameworks like TensorFlow or PyTorch are essential.

What types of projects might a research assistant machine learning typically work on?

As a Research Assistant in Machine Learning, you may be involved in projects such as developing and evaluating predictive models, processing and analyzing large datasets, and assisting in the publication of research findings. Your work could contribute to applications like natural language processing, computer vision, or recommendation systems, depending on the focus of the research group. You’ll often collaborate closely with senior researchers, data scientists, or PhD students, allowing you to participate in brainstorming sessions, code development, and experimental design. This experience provides valuable exposure to cutting-edge technology and can serve as a strong foundation for a research or industry career in machine learning.

What are the key skills and qualifications needed to thrive as a research assistant machine learning?

To thrive as a Research Assistant Machine Learning, you need a solid understanding of machine learning algorithms, programming skills (especially in Python or R), and a background in statistics or computer science, often supported by a bachelor’s or master’s degree. Experience with frameworks such as TensorFlow, PyTorch, and data analysis tools, as well as familiarity with version control systems like Git, is highly beneficial. Strong problem-solving abilities, attention to detail, and effective communication skills help you excel in collaborative research environments. These skills ensure you can contribute meaningfully to research projects, analyze complex datasets, and communicate findings effectively within interdisciplinary teams.

What are popular job titles related to Research Assistant Machine Learning jobs in Berkeley, CA?

For Research Assistant Machine Learning jobs in Berkeley, CA, the most frequently searched job titles are:

What job categories do people searching Research Assistant Machine Learning jobs in Berkeley, CA look for?

The top searched job categories for Research Assistant Machine Learning jobs in Berkeley, CA are:

What cities near Berkeley, CA are hiring for Research Assistant Machine Learning jobs?

Cities near Berkeley, CA with the most Research Assistant Machine Learning job openings:

Research Assistant Machine Learning jobs near you
Infographic showing various Research Assistant Machine Learning job openings in Berkeley, CA as of August 2026, with employment types broken down into 78% Full Time, and 22% Part Time. Highlights an 100% In-person job distribution, with an average salary of $55,799 per year, or $26.8 per hour.

Machine Learning Engineer, Reinforcement Learning

Skild AI

San Mateo, CA

Full-time

Re-posted 6 days ago

Job description

Position Overview

We are looking for a Machine Learning Engineer to be responsible for designing and implementing cutting-edge reinforcement learning algorithms, conducting experiments, and optimizing these models to perform efficiently in real-world robotic environments. This will require close collaboration with our robotics, research, and engineering team. Your work will directly impact the development of intelligent, adaptable robots capable of learning and performing complex tasks autonomously.

Responsibilities
  • Develop and implement state-of-the-art reinforcement learning algorithms for robotic applications.
  • Design and conduct experiments to train RL models and conduct real-world tests.
  • Collaborate closely with researchers to explore novel methods of scaling up reinforcement learning model training.
  • Communicate effectively with inference, application, and deployment engineers to integrate RL models into robotic systems and iterate on methods to enable robust deployment.
  • Analyze and interpret experimental results, iterating on model design to achieve desired performance.
  • Stay up-to-date with the latest research and advancements in reinforcement learning.
Preferred Qualifications
  • BS, MS or higher degree in Computer Science, Robotics, Engineering or a related field, or equivalent practical experience.
  • Proficiency in Python, C++, or similar and at least one deep learning library such as PyTorch, TensorFlow, JAX, etc.
  • Deep understanding and practical experience with various reinforcement learning algorithms and techniques (model-free, model-based, multi-task, hierarchical, multi-agent, etc.).
  • Strong background in algorithms, data structures, and software engineering principles.
  • Experience with physics simulation engines and tools for training RL.
  • Deep understanding of state-of-the-art machine learning techniques and models.
  • Extensive industry experience with reinforcement learning and robotic systems.

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