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Research Scientist Intern, Robotics

Burlingame, CA · Internship · Posted Oct 26, 2026

Education
Currently has, or is in the process of obtaining, a Ph.D. degree in Robotics, Computer Science, Computer Vision, Artificial Intelligence, Electrical/Mechanical Engineering, Controls, or a relevant technical field.
Visa sponsorship
Must obtain work authorization in the country of employment at the time of hire and maintain ongoing work authorization during employment.

About the job

Research Scientist Intern advancing robot learning and embodied intelligence through research, algorithm development, and experiments in simulation and on physical robots.

What you'll do

  • Develop and evaluate algorithms and learned policies for robot perception, manipulation, navigation, and control.
  • Conduct robot-learning research, including multimodal data learning, data collection, teleoperation, and sim-to-real transfer.
  • Collaborate across research and engineering teams and communicate or publish research results.

What they ask for

  • Currently pursuing or obtaining a Ph.D. in a relevant technical field; intend to return to the degree program after the internship.
  • Experience with a programming language and with machine-learning or deep-learning systems and frameworks.
  • Experience advancing AI for robotics or computer vision, including deploying learned systems on real robot hardware.
  • Must obtain and maintain work authorization in the country of employment; demonstrated research results, cross-functional teamwork, and analytical problem-solving experience.

Nice to have

  • Experience with simulation, domain randomization, and sim-to-real transfer.
  • Experience with classical robotics foundations, large-scale multimodal data, and real-world experiment evaluation.

Pay

$7,650/month to $12,667/month (compensation type not specified)

Tools

Python, C++, C, Java, ROS/ROS 2, MuJoCo, Isaac Sim/Lab, PyTorch

AI focus

Robot learning and embodied intelligence, including deep learning, foundation models, imitation and reinforcement learning, and vision-language-action models.

Model-written summary · the original posting is authoritative

First seen Oct 29, 2026 · Last verified Nov 5, 2026 (UTC)