The board
Internship
Human Interactive Driving Intern – World Models
Toyota Research Institute · Human Interactive Driving
- Hours
- Intern
- Where
- Los Altos, CA
- Posted
- Nov 14, 2025
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.
This is a paid 12-week internship opportunity and is a hybrid, in-office role.
Here’s a glimpse into the Internship experience from some of our TRI interns!
The Team
You’ll be joining a multidisciplinary research team focused on developing a world foundation model for driving—a unified, transferable representation of driving knowledge built from large-scale real-world and simulated data. Together, we are tackling the complex challenges of multi-agent interaction, causal reasoning, and embodied intelligence in highly dynamic, real-world driving environments.
What you'd do
- Conduct original research in one or more areas: world modeling, multi-agent interaction, reinforcement learning, perception, or simulation-to-reality transfer.
- Collaborate closely with full-time researchers on the design, training, and evaluation of learning-based driving systems.
- Contribute to building and experimenting with task-aware, multi-modal, and uncertainty-aware models.
- Develop and evaluate prototypes in closed-loop simulation environments and, time permitting, on high-performance autonomous driving hardware.
- Present research findings through internal talks and work towards a top-tier academic publication.
- Integrate and work with large-scale datasets (open-source and internal).
What they want
- Currently enrolled in a Ph.D. program in Computer Science, Robotics, Machine Learning, or a related field.
- Strong background in machine learning, particularly in areas such as deep learning, generative models, reinforcement learning, or probabilistic modeling.
- Demonstrated experience with one or more of the following: World models (e.g., latent dynamics, diffusion-based models), Model-based RL or decision-making, 3D perception or sensor fusion, and Large-scale simulation for robotics or autonomous systems.
- Prior publication(s) in top-tier conferences (NeurIPS, ICLR, ICML, CVPR, ICRA, CoRL, etc.)
- Proficiency with Python and PyTorch.
- Familiarity with AWS services (S3, EC2, and SageMaker) and open-source driving datasets (nuScenes, Waymo, Argoverse, etc.) is a plus.