Robotics Intern - Large Behavior Models, Policy Training
Toyota Research InstituteLos Altos, California
Internship
Posted October 13, 2025
$45 - $65/hr
Apply Now
Application opens on company website
Job Description
A research internship focused on developing and prototyping machine learning models for dexterous robot manipulation, utilizing multimodal data, simulation, and reinforcement learning techniques to advance general-purpose robotics capabilities.
Key Responsibilities
- Develop and implement code prototypes for robotics and machine learning models
- Conduct experiments with simulated and real robots to test policies and models
- Collaborate with team members to refine algorithms and approaches
- Participate in research and contribute to peer-reviewed publications
Requirements
- The candidate must be able to create working code prototypes and interact frequently with team members.
- The candidate must have the ability to run experiments with both simulated and real physical robots.
- The candidate must be comfortable working with both existing large static datasets and a growing dynamic corpus of robot data.
- The candidate must be pursuing or have completed a degree in a relevant field such as computer science, robotics, machine learning, or a related discipline.
- The candidate must have experience or knowledge in developing algorithms for learning robust policies leveraging multiple sensing modalities such as proprioception, images, and 3D representations.
- The candidate must have experience or knowledge in data annotation and filtering, including improving policies without collecting more data by using non-robotics data at scale, new training objectives, new data annotations, or filtered datasets.
- The candidate must have experience or knowledge in scaling learning approaches to large-scale models trained on diverse sources of data, including web-scale text, images, and video.
- The candidate must have experience or knowledge in structured hierarchical reasoning using learned models.
- The candidate must have experience or knowledge in leveraging test time compute for embodied applications.
- The candidate must have experience or knowledge in multimodal reasoning models and reinforcement learning for multimodal models.
- The candidate must have experience or knowledge in leveraging history and memory for learning policies for long context tasks.
- The candidate must have experience or knowledge in improving robustness and few-shot generalization by leveraging sub-optimal and self-play data.
- The candidate must have experience or knowledge in developing interactive agents that can reduce embodied and instructional ambiguity, seek help, and seek clarification.
- The candidate must be able to participate in publishing work to peer-reviewed venues.
- The candidate must be able to work in an in-office environment for the duration of the internship.
- The candidate must be available for a 12-week summer internship starting in summer 2026.
Benefits & Perks
Paid 12-week summer internship
In-office role
Pay range between $45 and $65 per hour (California-based roles)
Medical insurance
Dental insurance
Vision insurance
Paid time off including holiday pay and sick time
Ready to Apply?
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