AI Resident - Learning From Videos (LFV)
tri· Robotics
About this role
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 advancing the state of the art in AI, robotics, driving, and material sciences.
The Team
The Learning From Videos (LFV) team in the Robotics division focuses on the development of foundation models capable of leveraging large-scale multi-modal (RGB, depth, flow, semantics, bounding boxes, tactile, audio, etc) data from multiple domains (driving, robotics, indoors, outdoors, etc) to improve downstream task performance.
Our approach emphasizes training scalability: by learning from multiple modalities, models can develop useful data-driven priors about 3D geometry, physics, and dynamics for world understanding.
Our research interests include, but are not limited to:
Video Generation
World Models
4D Reconstruction
Multi-Modal Models
Multi-View Geometry
Data Augmentation
Video-Language-Action Models
We focus primarily on embodied applications and aim to tackle some of the hardest scientific challenges in spatio-temporal reasoning, enabling autonomous agents to operate in real-world, unstructured environments.
The AI Resident
This year-long AI Residency is a research-focused position designed for early-career researchers and engineers who are excited to work on ambitious problems in embodied AI. The resident will be deeply integrated into the LFV team, contributing to both ongoing and new research efforts in areas including:
4D World Models
Physical and Embodied Intelligence
Multi-Modal Learning
As an AI Resident, you will collaborate closely with researchers and engineers at TRI on high-risk, pushing forward our understanding of spatio-temporal reasoning and zero-shot generalization. This is a research-focused position, targeting the development of methods and techniques that can solve real-world problems.
We welcome you to join a positive, friendly, and enthusiastic team of researchers, where you will contribute to helping people gain and maintain independence, access, and mobility. We work closely with other Toyota affiliates, and actively collaborate towards research publications and the productization of our developed technologies.
Frequently Asked Questions
Is the salary disclosed for the AI Resident - Learning From Videos (LFV) position at tri?
The salary for this AI Resident - Learning From Videos (LFV) role at tri is not publicly listed. Click "Apply Now" to learn more about the compensation package on their official careers page.
Where is the AI Resident - Learning From Videos (LFV) position at tri located?
This AI Resident - Learning From Videos (LFV) role at tri is based in Los Altos, CA. The position is listed as on-site or hybrid. Check the full job description or apply directly to confirm the work arrangement.
Is the AI Resident - Learning From Videos (LFV) role at tri full-time or part-time?
This is listed as a Full time position. It is posted as a AI Resident - Learning From Videos (LFV) role in the Robotics department at tri.
Which team or department does the AI Resident - Learning From Videos (LFV) at tri belong to?
This AI Resident - Learning From Videos (LFV) position is part of the Robotics department at tri. See the full job description for more information about the team structure and responsibilities.
How do I apply for the AI Resident - Learning From Videos (LFV) position at tri?
Click the "Apply Now" button on this page. You will be redirected to tri's official application portal hosted on lever where you can submit your application directly.
When was the AI Resident - Learning From Videos (LFV) job at tri posted?
This AI Resident - Learning From Videos (LFV) position at tri was posted on Mar 17, 2026. Apply as soon as possible — early applications are often reviewed first.
AI Resident - Learning From Videos (LFV)
tri
You'll be redirected to tri's official application page on Lever.