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Robotics Research Assistant Jobs in Berkeley, CA

Droyd Robotics

Electrical Technician

San Francisco, CA · On-site

$58K - $104K/yr

About the team Droyd builds autonomous robotic systems that automate repetitive manual work in ... The electrical work at Droyd supports both R&D and production. The work ranges from one-off cable ...

Physical Intelligence

Robot Operator

San Francisco, CA · On-site

$25/hr

... research - Collaborative mindset and strong work ethic Nice to Have - Experience with robotics ... assist in workplaces, and improve quality of life. This is a rare opportunity to work at the ...

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Robotics Research Assistant information

What does a robotics research assistant do?

A Robotics Research Assistant typically supports research projects by helping design, build, and test robotic systems. They often assist with programming robots, collecting and analyzing data from experiments, and collaborating with researchers or engineers. Their responsibilities may also include conducting literature reviews, preparing reports, and maintaining laboratory equipment. This role is important in advancing robotics technology and innovation.

What are the key skills and qualifications needed to thrive as a robotics research assistant, and why are they important?

To thrive as a Robotics Research Assistant, you need a solid background in robotics, computer science, or engineering, with experience in programming languages like Python or C++ and a relevant degree. Familiarity with robotics platforms (such as ROS), simulation tools (like Gazebo or MATLAB), and data analysis software is typically required. Strong analytical thinking, problem-solving abilities, and effective collaboration and communication skills help you contribute meaningfully to research projects. These skills and qualities are vital for efficiently advancing robotics research, troubleshooting complex systems, and working successfully within interdisciplinary teams.

What are some common challenges faced by robotics research assistants during experimental testing and data collection?

Robotics Research Assistants often encounter challenges such as troubleshooting hardware malfunctions, ensuring consistent experimental setups, and managing large datasets for analysis. Because robotics experiments can be sensitive to environmental variables, maintaining repeatability and documenting procedures are crucial. Collaboration with other team members, such as engineers and programmers, is essential to quickly resolve issues and keep projects on track. Developing strong problem-solving skills and adaptability is key to overcoming these challenges and contributing effectively to research goals.

What are the most commonly searched types of Robotics Research jobs in Berkeley, CA?

The most popular types of Robotics Research jobs in Berkeley, CA are:

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

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

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

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

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

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

Robotics Research Assistant jobs near you
Infographic showing various Robotics Research Assistant job openings in Berkeley, CA as of August 2026, with employment types broken down into 4% Internship, 88% Full Time, 4% Part Time, and 4% Contract. Highlights an 85% In-person, and 15% Remote job distribution.

Research Scientist: Pretraining

Generalist AI, Inc

San Mateo, CA • On-site

$240K - $350K/yr

Full-time

Re-posted yesterday

Key responsibilities

  • Design and execute large-scale pretraining runs for robot foundation models using multimodal datasets.

  • Define model architectures, objectives, and training curricula across vision, action, state, and language data.

  • Collaborate with ML Infra and Systems teams to optimize cluster utilization, throughput, and reliability.

Job description

About Generalist
At Generalist, we are on a mission to build general intelligence for the physical world and make it useful to everyone. We believe the industries and homes of the future will depend on humans and machines working together in new ways. Robots can help us build more and get more done.
We build embodied foundation models, starting with a focus on dexterity. This requires advancing the frontiers of data, models, and hardware, to enable robots to intelligently interact with the physical world.
The company embraces both large-scale AI and robotics as core to its DNA. Our team of researchers, roboticists, and company builders come from OpenAI, Boston Dynamics, Google DeepMind, and other frontier labs-with a track record of shipping AI breakthroughs. Before Generalist, we pioneered large embodied multimodal models and vision-language-action models (PaLM-E, RT-2, Gemini Robotics), launched and scaled ChatGPT and GPT-4 to hundreds of millions of users, engineered the foundations of autonomous driving, built next-generation robots (Atlas, Spot, Stretch) and pushed the limits of what they can do (from parkour to manipulation, and testing robustness).
We are an equal opportunity employer, and we do not discriminate on the basis of race, religion, color, national origin, sex, sexual orientation, age, veteran status, disability, genetic information, or other applicable legally protected characteristic.
About the Role
You will build the base intelligence layer for robotics. We train large-scale robot foundation models from massive multimodal datasets spanning video, proprioception, action traces, language, and more. You will design and run the core large-scale training efforts that give our models fundamentally new general capabilities across embodiments, tasks, and environments. You will "live and breathe" all forms of robot data.
You'll be responsible for:
  • Designing and executing large-scale pretraining runs for robot foundation models (transformer- and diffusion-based architectures)
  • Defining model architectures, objectives, and training curricula across multimodal robotic data (vision, action, state, language)
  • Developing scalable data mixtures and sampling strategies across petabyte-scale datasets
  • Guiding data collection operations towards new directions, as well as sourcing new datasets
  • Running ablations to understand scaling laws, data quality effects, and architecture tradeoffs
  • Collaborating closely with ML Infra and Systems to push cluster utilization, throughput, and reliability
  • Turning raw robotic interaction data into generalizable model capabilities

You might thrive in this role if you:
  • Have deep experience training large transformer or diffusion models at scale (for generative models e.g. including language models, audio models, or video models)
  • Have led or significantly contributed to multi-node, multi-GPU distributed training efforts
  • Have worked on scaling laws, optimization dynamics, and large-model failure modes
  • Have strong PyTorch fundamentals and comfort debugging at every layer of the stack
  • Care about both empirical rigor and raw iteration speed
  • Are excited about building general-purpose robot intelligence from first principles

Apply