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hirly last saw it live on 1 September 2026. Similar roles are on the live board.

Tri

AI Resident - Learning From Videos (LFV)

Los Altos, CA

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Seniority
Mid level
Country
US
Work mode
On-site / unstated
First seen by hirly
1 Sept 2026

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the posting

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.

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AI Resident - Learning From Videos (LFV) at Tri — hirly