Machine Learning Research Scientist,… at Toyota… · Cambridge

Summary: Toyota Research Institute (TRI) is on a mission to improve the quality of human life through advanced AI and robotics. They are seeking a Research Scientist to develop intelligent systems for physical assembly, focusing on building end-to-end AI systems and evaluating modern machine learning approaches in manufacturing contexts. Responsibilities: - 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 Required Qualifications: - A PhD in a relevant field such as Computer Science, Robotics, Mechanical Engineering, or a related discipline, completed recently (or nearing completion), with some post-PhD or internship work experience - A demonstrated track record of implementing non-trivial learning systems — not just running baselines, but building pipelines and components from scratch - Hands-on experience with policy learning, reinforcement learning, or robot learning, with strong intuitions about what makes these approaches succeed or fail in practice - Proficiency in Python and comfort working across the full stack of a research project, from data processing to model training to evaluation - Genuine interest in how physical products are designed and manufactured Preferred Qualifications: - 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 Required Skills: Machine Learning, Reinforcement Learning, Policy Learning, Python, Research Project Full Stack, Physical Reasoning, Robot Learning, Large Language Models, Vision-Language Models, Agentic AI Frameworks, Robot Manipulation, Motion Planning, Sim-to-Real Transfer, Manufacturing Processes, Assembly Planning, CAD/CAM Toolchains, Research Codebase Development Benefits: Medical, dental, and vision insurance, 401(k) eligibility, Paid time off benefits (including vacation, sick time, and parental leave), Annual cash bonus structure