Human Interactive Driving Research Intern, World Models
Description
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 will be joining the Extreme Performance Intelligent Control (EPIC) team in the Human Interactive Driving division, 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. Our approach is inspired by cutting-edge generative modeling techniques and powered by scalable infrastructure and open-source data, and we work closely with engineers to deploy our models in simulation and on hardware.
The Internship
As a Ph.D. Research Intern, you will conduct original research at the intersection of machine learning and autonomous driving. Your work will focus on advancing the state of the art in world modeling across various areas, including representation learning, action conditioning, and evaluation. You will have the opportunity to prototype and evaluate your ideas in closed-loop simulations and contribute to research publications alongside TRI scientists. This is an opportunity to test and refine your research in a collaborative, high-impact environment, while working with real-world data and contributing to the future of autonomous systems.
Responsibilities
- Conduct original research in one or more areas: world modeling, multi-agent interaction, reinforcement learning, perception, or sim-to-real transfer.
- Collaborate closely with full-time researchers on the design, training, and evaluation of learning-based driving systems.
- 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).
Qualifications
- Currently pursuing a Ph.D. in Computer Science, Robotics, Machine Learning, Electrical Engineering, or related fields.
- Strong background in machine learning, particularly in areas such as deep learning, generative models, reinforcement learning, or probabilistic modeling.
- Hands-on experience training and evaluating world models, model-based reinforcement learning, 3D reconstruction or sensor fusion, and large-scale simulation for robotics or autonomous systems.
- Proficient coding skills with expertise in modern deep learning frameworks (e.g., PyTorch, JAX, TensorFlow, etc.).
- Prior publication(s) in top-tier AI/ML conferences.
Bonus Qualifications
- Probabilistic and generative modeling.
- Autonomous driving datasets.
- Open-source foundation models.
- Amazon Web Services (e.g., S3, EC2, SageMaker, etc.).
Skills
As published by lever · 8 questions · 1 written answer
Basics
Resume/CV, Full name, Email, Phone, Current location, Current company, LinkedIn URL, Twitter URL, GitHub URL, Portfolio URL, Other website, Do you consider yourself a member of the Lesbian, Gay, Bisexual and/or Transgender, Queer and Questioning (LGBTQ) community?
Short answers (1)
- If you selected “Other” please share more details. optional
Pick from a list (6)
- How did you hear about this internship?
- What degree are you currently enrolled in?
- Are you eligible to work in the United States?
- Are you a U.S. citizen, a lawful permanent resident of the United States (“green card holder”), an asylee, a refugee, or temporary resident under the 1986 legalization program?
- Are you a national, citizen, or permanent resident of Cuba, Iran, North Korea, Sudan, Syria, or Crimea (region of Ukraine)?
- Selection criteria should be part of the application process and be provided in writing to all candidates on a consistent basis. TRI is committed to compliance with U.S. and other applicable export control laws. Under U.S. export control laws, the release or disclosure of U.S.-origin controlled technology to foreign nationals is deemed to be an export or re-export to the foreign nationals’ home countries. This “deemed export” rule does not apply to technology transfers between and among U.S. citizens, persons lawfully admitted for U.S. permanent residence, persons granted U.S. asylum or refugee status, or temporary residents under the 1986 legalization program. Your answers will be used by the company solely to ensure compliance with U.S. export control laws.
Written answers (1)
- In 1-3 sentences, tell us about one thing TRI is working on that you find exciting?