Robotics Intern - Large Behavior Models bei Tri
Tri · Los Altos, Vereinigte Staaten Von Amerika · Hybrid
- Optionales Büro in Los Altos
At Toyota Research Institute (TRI), we’re on a mission to improve the quality of human life. We’re developing new tools and capabilities to amplify the human experience. To lead this transformative shift in mobility, we’ve built a world-class team in Automated Driving, Energy & Materials, Human-Centered AI, Human Interactive Driving, Large Behavior Models, and Robotics.
This is a summer 2026 paid 12-week internship opportunity. Please note that this internship will be an in-office role.
The Mission
We are working to create general-purpose robots capable of accomplishing a wide variety of dexterous tasks. To do this, our team is building general-purpose machine learning foundation models for dexterous robot manipulation. These models, which we call Large Behavior Models (LBMs), use generative AI techniques to produce robot action from sensor data and human request. To accomplish this, we are creating a large curriculum of embodied robot demonstration data and combining that data with a rich corpus of internet-scale text, image, and video data. We are also using high-quality simulation to augment real world robot data with procedurally-generated synthetic demonstrations.
The Team
The Robotics Machine Learning Team’s charter is to push the frontiers of research in robotics and machine learning to develop the future capabilities required for general-purpose robots able to operate in unstructured environments such as homes or factories.
The Internship
We have several research thrusts under our broad mission, and we are looking for a research intern in any of these areas:
Data-efficient and general algorithms for learning robust policies leveraging multiple sensing modalities: proprioception, images, 3D representations, force, and dense tactile sensing.
Scaling learning approaches to large-scale models trained on diverse sources of data including web-scale text, images, and video.
Leveraging test time compute for embodied applications.
Quick and efficient improvement of learned policies.
MultiModal Reasoning Models.
Structured hierarchical reasoning using learned models.
Reinforcement Learning for MultiModal models.
Leveraging history and memory for learning policies for long context tasks.
Improving robustness and few-shot generalization by leveraging sub-optimal and self-play data.
Interactive agents that can reduce the embodied and instructional ambiguity and can seek help and clarification.
The intern who joins our team will be expected to create working code prototypes, interact frequently with team members, run experiments with both simulated and real (physical) robots, and participate in publishing the work to peer-reviewed venues. We’re looking for an intern who is comfortable working with both existing large static datasets as well as a growing dynamic corpus of robot data.
At Toyota Research Institute (TRI), we’re on a mission to improve the quality of human life. We’re developing new tools and capabilities to amplify the human experience. To lead this transformative shift in mobility, we’ve built a world-class team in Automated Driving, Energy & Materials, Human-Centered AI, Human Interactive Driving, Large Behavior Models, and Robotics.This is a summer 2026 paid 12-week internship opportunity. Please note that this internship will be an in-office role.The MissionWe are working to create general-purpose robots capable of accomplishing a wide variety of dexterous tasks. To do this, our team is building general-purpose machine learning foundation models for dexterous robot manipulation. These models, which we call Large Behavior Models (LBMs), use generative AI techniques to produce robot action from sensor data and human request. To accomplish this, we are creating a large curriculum of embodied robot demonstration data and combining that data with a rich corpus of internet-scale text, image, and video data. We are also using high-quality simulation to augment real world robot data with procedurally-generated synthetic demonstrations.The TeamThe Robotics Machine Learning Team’s charter is to push the frontiers of research in robotics and machine learning to develop the future capabilities required for general-purpose robots able to operate in unstructured environments such as homes or factories.The InternshipWe have several research thrusts under our broad mission, and we are looking for a research intern in any of these areas:Data-efficient and general algorithms for learning robust policies leveraging multiple sensing modalities: proprioception, images, 3D representations, force, and dense tactile sensing.Scaling learning approaches to large-scale models trained on diverse sources of data including web-scale text, images, and video.Leveraging test time compute for embodied applications.Quick and efficient improvement of learned policies.MultiModal Reasoning Models.Structured hierarchical reasoning using learned models.Reinforcement Learning for MultiModal models.Leveraging history and memory for learning policies for long context tasks.Improving robustness and few-shot generalization by leveraging sub-optimal and self-play data. Interactive agents that can reduce the embodied and instructional ambiguity and can seek help and clarification. The intern who joins our team will be expected to create working code prototypes, interact frequently with team members, run experiments with both simulated and real (physical) robots, and participate in publishing the work to peer-reviewed venues. We’re looking for an intern who is comfortable working with both existing large static datasets as well as a growing dynamic corpus of robot data.
Qualifications
Bonus Qualifications
The pay range for this position at commencement of employment is expected to be between $45 and $65/hour for California-based roles; however, base pay offered may vary depending on multiple individualized factors, including market location, job-related knowledge, skills, and experience. Note that TRI offers a generous benefits package including vacation and sick time. Details of participation in these benefit plans will be provided if an employee receives an offer of employment.
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