Robotics Intern - Post-Training Policy Adaptation

Toyota Research Institute Inc.; Los Altos (CA); Hybrid; USD 62,000 - 90,000; Full time

Benefits offered by this job

Medical, dental, and vision insurance

Paid time off (including holiday and s

Job summary

Toyota Research Institute offers a 12-week paid internship in a hybrid in-office setting in California. The Robotics division studies pretrained generalist policies, with a focus on adapting them to diverse tasks, environments, and hardware.

The role targets PhD candidates in CS/ML/Robotics with experience in robot learning, reinforcement learning, simulation, and Python/PyTorch. Excellent collaboration and communication skills are expected as data-driven research is shared internally and in

Qualifications

• Currently pursuing a Ph.D. in Computer Science, Machine Learning, Robotics, or a related field.
• Research experience in robot learning, reinforcement learning, imitation learning, generative modeling, world models, or a related area.
• Interest in open research problems involving large-scale machine learning grounded in physical systems.
• Proficiency in Python and a deep-learning framework such as PyTorch.
• Ability to collaborate effectively with researchers and engineers and communicate research findings clearly.

Responsibilities

• Develop post-training methods that adapt pretrained generalist robot policies to new tasks, environments, and robotic systems.
• Design and conduct rigorous experiments in simulation and, where appropriate, on real robotic systems.
• Analyze results, communicate findings, and contribute to research publications and internal technical reports.

Skills

Python

PyTorch

Research collaboration

Communication

Education

Ph.D. in Computer Science, ML, Robotics, or related field

Job description

Toyota Research Institute offers a 12-week paid internship in a hybrid in-office setting in California. The Robotics division studies pretrained generalist policies, with a focus on adapting them to diverse tasks, environments, and hardware.

The role targets PhD candidates in CS/ML/Robotics with experience in robot learning, reinforcement learning, simulation, and Python/PyTorch. Excellent collaboration and communication skills are expected as data-driven research is shared internally and in