Role overview
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 Future Factory team in TRI's Energy and Materials division focuses on developing cutting-edge tools and methods to accelerate change and increase flexibility and efficiency in Toyota's product design and manufacturing, to speed the transition to an emissions-free world. To achieve this we are building end-to-end AI systems that can reason about how physical objects are made — from design intent through to the assembly of real parts — and developing the learning infrastructure needed to train and evaluate these systems at scale.
What you'll work on
- Design and implement end-to-end modeling pipelines for machine assembly tasks, building from the ground up rather than adapting existing frameworks.
- Run systematic experiments to evaluate architectural variants, data collection and curation strategies, and a range of supervised and reinforcement learning techniques for physical manipulation.
- Develop and maintain rigorous evaluation protocols to measure policy performance across assembly scenarios, including generalization to novel parts, configurations, and failure modes.
- Explore how modern LLMs and agentic systems can be integrated to support physical reasoning and task planning in assembly contexts.
- Collaborate with researchers and engineers across TRI and Toyota's broader ecosystem to connect learning-based systems with real hardware and manufacturing workflows.
- Contribute to writing and publishing research results in peer-reviewed venues.
What we're looking for
- Familiarity with large language models, vision-language models, or agentic AI frameworks, particularly in contexts involving structured reasoning or tool use.
- Experience with robot manipulation, motion planning, or sim-to-real transfer.
- Exposure to manufacturing processes, assembly planning, or CAD/CAM toolchains.
- Experience building or contributing to production-level research codebases.
The pay range for this position at commencement of employment is expected to be between $176,000 and $253,000/year for California-based roles, and between $158,400 and $227,700/year for Massachusetts-based roles. Base pay offered will depend on multiple individualized factors, including, but not limited to, a candidate's experience, skills, job-related knowledge, and market location. TRI offers a generous benefits package including medical, dental, and vision insurance, 401(k) eligibility, paid time off benefits (including vacation, sick time, and parental leave), and an annual cash bonus structure. Additional details regarding these benefit plans will be provided if an employee receives an offer of employment.
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