Toyota Research Institute

About the Company

At Toyota Research Institute (TRI), we're conducting research to amplify human ability, focusing on making our lives safer and more sustainable. Led by Dr. Gill Pratt, TRI's team of researchers develops technologies to advance automated driving, energy and materials, human-centered artificial intelligence, human interactive driving, large behavior models, and robotics. We're dedicated to building a world of "mobility for all" where everyone, regardless of age or ability, can live in harmony with technology to enjoy a better life. Through innovations in AI, we will: - Develop technology for vehicles and robots to help people enjoy new levels of independence, access, and mobility. - Bring advanced mobility technology to market faster. - Discover new materials that will make batteries and hydrogen fuel cells smaller, lighter, less expensive, and more powerful. Our work is guided by a dedication to safety - in how we research, develop, and validate the performance of vehicle technology to benefit society. As a subsidiary of Toyota, TRI is fueled by a diverse and inclusive community of people who carry invaluable leadership, experience, and ideas from industry-leading companies. Over half of our technical team holds PhD degrees. We're continually searching for the world's best talent - people who are ready to define the new world of mobility with us! We strive to build a company that helps our people thrive, achieve work-life balance, and bring their best selves to work. At TRI, you will have the opportunity to enjoy the best of both worlds - a fun start-up environment with brilliant people who enjoy solving tough problems and the financial backing to successfully achieve our goals. Come work with TRI if you're interested in transforming mobility through designing safer cars, enabling the elderly to age in place, or designing alternative fuel sources. Start your impossible with us.

Listed Jobs

Company Name

Toyota Research Institute

Job Title

Robotics Intern - Learning from Humans & Language Steering

Job Description

**Job Title:** Robotics Intern – Learning from Humans & Language Steering **Role Summary:** Summer 2026, 12‑week paid internship focused on developing large behavior models (LBMs) for dexterous robotic manipulation. Interns will train and evaluate machine learning systems that translate egocentric human video, multimodal data, and natural language into robotic actions, and will prototype code, run simulations and physical robot experiments, and contribute to research publications. **Expectations:** - Deliver functional code prototypes and experiments for robot perception, grounding, and instruction following. - Collaborate with researchers to design data pipelines and model architectures for large, heterogeneous datasets. - Participate in design reviews, write technical reports, and co‑author papers for peer‑reviewed conferences or journals. - Maintain rigorous documentation and adhere to best software practices in a fast‑moving research setting. **Key Responsibilities:** 1. Build and refine learning pipelines that map first‑person human video and sensor data to robotic control policies (e.g., RL, offline RL, behavior cloning). 2. Pre‑train and fine‑tune robot foundation models on large-scale multimodal corpora (text, image, video). 3. Develop methods for instruction following, grounding natural language and multimodal commands within LBM frameworks. 4. Design interactive learning experiments where robots query humans to clarify ambiguous goals or instructions. 5. Collect, filter, and augment real‑world robotic demonstration data, including synthetic procedural simulations. 6. Create scalable data pipelines and evaluate model performance on both simulated and physical robot platforms. **Required Skills:** - Python programming (proficient, with experience in deep learning frameworks such as PyTorch or TensorFlow). - Machine learning for robotics: RL, offline RL, behavior cloning, or familiarity with large multimodal datasets/models. - Experience prototyping and deploying models in simulation and on physical robots. - Strong problem‑solving skills and a “make it happen” attitude. - Ability to communicate technical findings clearly in written reports and presentations. **Required Education & Certifications:** - Current enrollment in an undergraduate or graduate program in Computer Science, Robotics, Electrical Engineering, or related field. - No specific certifications required, but knowledge of robotics control, reinforcement learning, and multimodal learning is essential.

Cambridge, United states

Hybrid

Fresher

11-11-2025

Company Name

Toyota Research Institute

Job Title

Robotics Intern - Large Behavior Models

Job Description

**Job title:** Robotics Intern – Large Behavior Models **Role Summary:** 12‑week paid internship focused on building and training large behavior models (LBMs) for dexterous robotic manipulation. The role blends machine learning, multimodal data integration, simulation, and real‑robot experimentation to advance general‑purpose robots. **Expactations:** Deliver working code prototypes, run experiments on simulated and physical robots, contribute to research publications, and collaborate closely with a multidisciplinary robotics‑ML team. **Key Responsibilities:** - Design, implement, and evaluate ML models for robotic control using proprioception, vision, 3‑D, force, and tactile data. - Integrate and curate large multimodal datasets (text, image, video, and robot demonstration data) for LBM training. - Scale learning approaches to web‑scale datasets and large‑parameter models. - Conduct rapid prototyping and iterative testing in simulation and on real robots. - Analyze experimental results, refine models, and document findings for peer‑reviewed venues. - Participate in team discussions, knowledge sharing, and code reviews. **Required Skills:** - Proficiency in Python and software development best practices. - Hands‑on experience with learning‑for‑control methods: reinforcement learning, offline RL, or behavior cloning. - Familiarity with large multimodal datasets, pre‑trained models, or multimodal reasoning. - Ability to prototype quickly, debug, and optimize code. - Comfortable working with simulation environments and physical robotic platforms. - Strong analytical and communication skills. **Bonus Skills:** Hardware interfacing, robotics firmware, or embedded systems experience. **Required Education & Certifications:** - Current enrollment or recent graduate in Robotics, Computer Science, Electrical Engineering, or a closely related field. - Coursework or research experience in machine learning, deep RL, multimodal learning, or robotic manipulation. ---

Los altos, United states

Hybrid

Fresher

11-11-2025

Company Name

Toyota Research Institute

Job Title

Research Scientist, World Models – Policy Training and Evaluation

Job Description

**Job Title:** Research Scientist, World Models – Policy Training and Evaluation **Role Summary** Develop scalable, human-like driving intelligence for autonomous systems by creating data-driven world models that support multi-agent reasoning and robust policy optimization in dynamic environments. **Expectations** - Refine world models for policy learning, counterfactual reasoning, and scenario generation. - Design methods to integrate world models with reinforcement learning (RL), imitation learning, and offline policy evaluation. - Synthesize high-risk, edge-case scenarios to stress-test autonomous driving policies. - Explore advanced techniques (latent-space simulation, model distillation, differentiable simulation) to enhance policy development pipelines. - Collaborate across research teams to align world modeling with planning, safety evaluation, and long-horizon decision-making goals. - Publish high-impact research in AI/ML/robotics conferences (e.g., NeurIPS, ICML) and contribute open-source tools. **Key Responsibilities** - Architect and train world models for policy training and evaluation in autonomous driving systems. - Implement and evaluate world model adaptation, fine-tuning, and safety-critical policy optimization techniques. - Develop simulation frameworks for stress-testing policies in diverse, realistic scenarios. - Co-design cross-disciplinary architectures to model agent-environment dynamics for robust decision-making. - Validate models in simulated and real-world environments for autonomy applications. **Required Skills** - Expertise in world modeling, model-based reinforcement learning (MBRL), and offline/imitation learning. - Proficiency in latent dynamics models (e.g., Dreamer, MuZero) and uncertainty/generalization in learned environments. - Strong software development skills in Python (PyTorch, JAX) for ML research. - Experience in autonomous vehicle policy evaluation, simulation-to-reality transfer, and safety assurance. - Track record in ML/robotics research with publications in top-tier conferences (e.g., ICLR, CoRL). **Required Education & Certifications** - PhD in Computer Science, Robotics, Machine Learning, or related field. - Demonstrated mastery in two or more of the following: world model adaptation, MBRL, simulation techniques, or policy evaluation.

Los altos, United states

Hybrid

13-11-2025

Company Name

Toyota Research Institute

Job Title

Human Interactive Driving Research Intern, Machine Learning & Optimization

Job Description

**Job Title** Human Interactive Driving Research Intern, Machine Learning & Optimization **Role Summary** A 12‑week paid summer internship (Hybrid) focused on applying mathematical optimization and machine‑learning techniques to human‑interactive driving and other automated‑driving research challenges. The internship supports research projects aimed at publishing in top-tier venues and involves collaborative work with the Optimization and HID teams. **Expectations** - Conduct independent, high‑impact research under mentorship, with the goal of producing a publishable result. - Manage timelines and deliverables in a dynamic, fast‑pacing environment. - Collaborate effectively with cross‑functional stakeholders (researchers, engineers, and other interns). **Key Responsibilities** - Define project scope and align objectives with mentor and team. - Execute a well‑scoped research project, from hypothesis through experimentation to manuscript preparation. - Target publication in leading venues such as NeurIPS, ICML, ICLR, SIOPT, or Math Programming. - Prioritize tasks, meet deadlines, and self‑manage workload. - Coordinate with other team members and stakeholders to integrate research findings into broader initiatives. **Required Skills** - Current Ph.D. candidate in machine learning / AI, optimization, computer science, applied mathematics, or equivalent. - Demonstrated publication record in relevant conferences or journals. - Proficient programming in Python with PyTorch and Linux command line. - Experience with distributed computing environments (e.g., AWS, Azure, GCP) is a plus. - Strong analytical and problem‑solving abilities. - Excellent written and oral communication; ability to work collaboratively. **Required Education & Certifications** - Enrolled in a Ph.D. program in ML/AI, optimization, computer science, applied mathematics, or a closely related discipline. (No additional certifications required.) *Note: Applicants should include a Google Scholar link in their CV to provide a full list of publications.*

Cambridge, United states

Hybrid

Fresher

12-11-2025