Research Scientist, Robot Learning

Toyota Research Institute•Cambridge, MA

11h

About The Position

Toyota Research Institute (TRI) is seeking a driven researcher to advance robot learning as part of a cross-functional team working across hardware, simulation, perception, controls, and machine learning. The team aims to develop general-purpose robots that operate reliably in unstructured environments and work effectively alongside people. Its work emphasizes fundamental capability development, open-source software, and research publications. The role focuses on advancing robot learning models using language, video, action, and multimodal data. The researcher will develop and implement methods for robot behavior learning, contribute to internal capabilities and high-impact publications, and collaborate with TRI researchers, engineers, and partner academic laboratories. The position calls for someone able to work independently and collaboratively, and to shift between rapid prototyping and robust implementation. For Massachusetts-based roles, the expected base pay at commencement is $158,400–$227,700 per year. Actual pay depends on individualized factors such as experience, skills, job-related knowledge, and market location. TRI offers medical, dental, and vision insurance, 401(k) eligibility, paid time off including vacation, sick time, and parental leave, and an annual cash bonus structure. TRI describes its community as diverse and inclusive and provides equal employment opportunity.

Requirements

PhD in computer science, machine learning, robotics, or a closely related field.
Experience training large models and deploying them on embodied systems, particularly for robotic manipulation.
Strong software development skills in Python, familiarity with mixed C++/Python codebases, and a focus on clean, maintainable code.
Extensive practical experience with machine learning using a major framework such as PyTorch or TensorFlow.
Familiarity with data pipelines, model serving and optimization, cloud training, and dataset management.
Strong understanding of state-of-the-art robot learning, including generative models such as diffusion policy or flow matching, reinforcement learning, and/or world models.
Practical experience with robots and system integration challenges involved in research and deployment on physical hardware platforms.
Ability to work quickly and switch between rapid prototyping and robust implementation as needed.
Strong record of impact through first-author publications at top-tier machine learning or robotics conferences, or meaningful contributions to successful industry initiatives.

Nice To Haves

Experience in robotics and machine learning research or related projects in an industry setting.
Experience with robotic middleware such as ROS 2 and common communication methods and protocols.
Experience with modern machine learning infrastructure pipelines, approaches, and tools.
Experience with VR-based teleoperation for real-time robot control.
Background or familiarity with motion control and actuation, whole-body control, reinforcement learning, robot teleoperation methods, common communication protocols, research robotic arms or systems, visual perception and depth sensors, machine learning, robotic simulation, force and tactile sensing systems, or haptic interfaces.

Responsibilities

Work as part of a closely-knit research team advancing robot capabilities.
Study and advance robot learning models, including models using language, video, action, and multimodal data.
Implement, extend, and create state-of-the-art methods for robot behavior learning, including reinforcement learning and imitation learning.
Contribute to rapid progress through development of internal capabilities and high-impact external publications.
Collaborate with internal research scientists and engineers and partner laboratories at academic research universities.