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Computer Science Research Assistant Jobs in Fremont, CA

Generalist AI, Inc

Research Assistant

San Mateo, CA · On-site

$150K - $200K/yr

We are looking for a Research Assistant to help design, run, and analyze experiments at the ... Research Scientist. At Generalist, we are building foundation models for robots. These models ...

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How much do computer science research assistant jobs pay per hour?

As of Aug 24, 2026, the average hourly pay for computer science research assistant in Fremont, CA is $23.98, according to ZipRecruiter salary data. Most workers in this role earn between $20.24 and $27.88 per hour, depending on experience, location, and employer.

What is a computer science research assistant?

A Computer Science Research Assistant supports professors or researchers in conducting experiments, analyzing data, and developing software or algorithms. They may assist with literature reviews, coding, debugging, or testing to advance research projects. The role often involves working with programming languages, machine learning, cybersecurity, or other specialized topics. It provides valuable experience for students or professionals looking to deepen their knowledge in the field.

What are the typical duties and daily responsibilities of a computer science research assistant?

As a Computer Science Research Assistant, your daily responsibilities often include assisting with data collection and analysis, developing or testing software prototypes, conducting literature reviews, and helping prepare reports or presentations for research findings. You may also collaborate closely with faculty, graduate students, or industry partners, contributing to coding tasks, experimental setups, and troubleshooting technical issues as they arise. The role frequently involves both independent problem-solving and teamwork, providing a supportive environment to deepen technical skills and gain hands-on research experience. This position is an excellent opportunity to develop your research portfolio, learn advanced computing concepts, and prepare for potential graduate study or specialized tech careers.

What are the key skills and qualifications needed to thrive as a computer science research assistant?

To thrive as a Computer Science Research Assistant, you need strong analytical skills, proficiency in programming languages (such as Python, Java, or C++), and a solid understanding of algorithms and data structures, usually evidenced by coursework or a relevant degree. Familiarity with research tools, version control systems (like Git), and possibly certifications in data analysis or machine learning are advantageous. Excellent problem-solving abilities, attention to detail, and effective written and verbal communication help individuals excel when collaborating on research projects. These competencies enable you to support rigorous research, contribute to innovative solutions, and work efficiently as part of an academic or industry research team.

What are the most commonly searched types of Computer Science Research jobs in Fremont, CA?

The most popular types of Computer Science Research jobs in Fremont, CA are:

What job categories do people searching Computer Science Research Assistant jobs in Fremont, CA look for?

The top searched job categories for Computer Science Research Assistant jobs in Fremont, CA are:

What cities near Fremont, CA are hiring for Computer Science Research Assistant jobs?

Cities near Fremont, CA with the most Computer Science Research Assistant job openings:

Computer Science Research Assistant jobs near you
Infographic showing various Computer Science Research Assistant job openings in Fremont, CA as of August 2026, with employment types broken down into 1% As Needed, 83% Full Time, 12% Part Time, 3% Contract, and 1% Nights. Highlights an 79% Physical, 2% Hybrid, and 19% Remote job distribution, with an average salary of $49,885 per year, or $24 per hour.

Research Assistant

Generalist AI, Inc

San Mateo, CA • On-site

$150K - $200K/yr

Full-time

Re-posted 28 days ago

Job description

About the Role:
We are looking for a Research Assistant to help design, run, and analyze experiments at the intersection of machine learning and robotics. This is an entry-level research role for individuals with less than 3 years of research experience, and is designed to be a potential career path towards eventually contributing as a Research Scientist.
At Generalist, we are building foundation models for robots. These models improve through a tight feedback loop: design experiments, collect data, train or fine-tune models, evaluate them in the real world, analyze results, and repeat. This role helps make that loop faster, more rigorous, and more reliable.
You will work closely with ML researchers and robotics engineers to run robot experiments, design evaluation tasks, brainstorm ideas, collect data, interpret results, and document repeatable workflows.
A major part of this role is helping ensure our evaluations are trustworthy. We care deeply about experimental design, controls, hands-on iteration, sample sizes, variance, repeatability, and statistical rigor.
You'll be responsible for:
  • Running structured experiments on robot platforms
  • Setting up physical tasks, materials, fixtures, and benchmarks for robot evaluations
  • Collecting high-quality robot data and tracking experimental conditions
  • Measuring real-world success rates across tasks, robots, and model variants
  • Designing evaluations with attention to controls, repeatability, statistical rigor, and sources of bias
  • Analyzing results to help distinguish real model improvements from noise
  • Synthesizing findings and communicating them clearly to ML researchers and engineers
  • Preparing robots, sensors, workspaces, and materials for rollouts and evaluations
  • Helping kick off training jobs, run evaluations, and organize results
  • Beta testing internal and third-party tools for teaching robots new skills
  • Troubleshooting physical setups, hardware issues, and procedural bottlenecks
  • Writing clear documentation and playbooks so others can reproduce workflows
  • Improving experimental reliability, data quality, and operational throughput over time
You might thrive in this role if you:
  • Have experience running experiments, lab studies, field studies, data collection workflows, or structured evaluations
  • Think carefully about experimental design, confounding factors, controls, sample sizes, variance, and what conclusions the data can actually support
  • Are diligent and detail-oriented, especially when tasks are repetitive but subtle differences matter
  • Enjoy hands-on work with physical systems, equipment, materials, or instruments
  • Are comfortable following protocols while also noticing when something is wrong or could be improved
  • Can coordinate many moving parts: robots, materials, tasks, data, model versions, metrics, and documentation
  • Communicate clearly and can summarize what happened, what changed, and what the evidence suggests
  • Are curious about machine learning and robotics, even if you are not yet an expert in either
  • Have some exposure to programming, data analysis, robotics, hardware, electronics, mechanical assembly, or experimental tooling
  • Prefer fast iteration, careful measurement, and empirical progress over abstract theory alone
About Generalist
At Generalist, we are on a mission to make general-purpose robots a reality. 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.

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