Research Intern

Job Description

Here is the detailed, enriched job description for the TRI Research Intern position:

About Toyota Research Institute (TRI)

At TRI, we are driven by a mission to improve the quality of human life by developing new tools and capabilities that amplify the human experience. We foster a world-class team advancing the state of the art in AI, robotics, driving, and material sciences to lead the transformative shift in mobility.

Internship Details:

• This is a Summer 2026 opportunity.
• Duration: 12-week internship.
• Compensation: This is a paid internship.
• Location: This will be an in-office role in Cambridge, MA.

The Mission:

We are dedicated to creating general-purpose robots capable of accomplishing a wide variety of dexterous tasks. Our team builds general-purpose machine learning foundation models for dexterous robot manipulation, referred to as Large Behavior Models. These models leverage generative AI techniques to produce robot actions from sensor data and human requests. Our approach involves:

• Creating a large curriculum of embodied robot demonstration data.
• Combining this data with a rich corpus of internet-scale text, image, and video data.
• Utilizing high-quality simulation to augment real-world robot data with procedurally-generated synthetic demonstrations.

The Challenge:

We envision a future where robots provide assistance with household chores and cooking, help older individuals maintain independence, and enable people to dedicate more time to enjoyable activities. To achieve this, robots must operate reliably in messy, unstructured environments. Our core question is: “What will it take to create truly general-purpose robots that can accomplish a wide variety of tasks in settings like human homes with minimal human supervision?” We believe the solution lies in leveraging large-scale datasets of physical interaction from diverse sources and applying the latest advances in machine learning to learn general-purpose robot behaviors.

The Internship: Focus Areas & Expectations

We are seeking a research intern to contribute to several key research thrusts under our broad mission.

Research Thrusts:

• Developing data-efficient and general algorithms for learning robust policies, leveraging multiple sensing modalities such as proprioception, images, force, and dense tactile sensing.
• Scaling learning approaches to large-scale models trained on diverse sources of data, including web-scale text, images, and video.
• Focusing on quick and efficient improvement of learned policies.
• Developing and deploying learned policies on complex mobile manipulator embodiments, such as humanoid robots.

Intern Expectations:

The intern joining our team will be expected to:

• Create working code prototypes.
• Interact frequently with team members.
• Run experiments with both simulated and real (physical) robots.
• Participate in publishing the work to peer-reviewed venues.
• Be comfortable working with both existing large static datasets and a growing, dynamic corpus of robot data.

Specific Areas of Focus Include:

• Vision-Language-Action (VLA) models for mobile manipulation
• Dynamic whole-body manipulation on humanoids
• Cross-embodiment transfer
• Universal (UMI-style or ego-centric) data collection methods
• Haptic/tactile-inclusive VLA models
• Integration of VLA policy methods with model-based robotics methods
• Large-scale synthetic data generation and sim-to-real transfer
• Post-training for continual learning

Qualifications:

• Currently pursuing a degree (Ph.D., M.S.) in Robotics, Computer Science, Mechanical Engineering, or a related field.
• Publication record at top-tier robotics/ML conferences (e.g., RSS, CoRL, ICRA, NeurIPS, ICML, ICLR, CVPR, ICCV).
• Hardware experience is strongly preferred, especially toward deploying learned policies on real robotic systems.
• Experience with machine learning and familiarity with large datasets and models.
• Strong software development skills in Python. Experience in C++ is very helpful, but not strictly required.
• A “make it happen” attitude and comfort with fast prototyping and running informative experiments.
• A passion for robotics and doing research grounded in important fundamental problems.

Bonus Qualifications:

• Hands-on experience with using machine learning for learned control, including behavior cloning and/or reinforcement learning, for manipulation.
• Hardware experience is strongly preferred, especially toward deploying learned policies on real robotic systems.
• Experience with machine learning and familiarity with large datasets, models, and benchmarks.
• System integration skills, including using state-of-the-art ML tools, databases, etc.

Compensation & Benefits:

The pay range for this position at the commencement of employment is expected to be between $40 and $58/hour for Massachusetts-based roles. Base pay offered will depend on multiple individualized factors, including, but not limited to, business or organizational needs, market location, job-related knowledge, skills, and experience.
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).
• An annual cash bonus structure.

Additional details regarding these benefit plans will be provided if an employee receives an offer of employment.

Legal & Company Policies:

We reference a Candidate Privacy Notice to inform you of the categories of personal information collected from individuals who inquire about and/or apply to work for Toyota Research Institute, Inc. or its subsidiaries, and the purposes for which such personal information is used.

TRI is fueled by a diverse and inclusive community and is dedicated to fostering an innovative and collaborative environment. We believe diversity makes us stronger and are proud to provide Equal Employment Opportunity for all, without regard to an applicant’s race, color, creed, gender, gender identity or expression, sexual orientation, national origin, age, physical or mental disability, medical condition, religion, marital status, genetic information, veteran status, or any other status protected under federal, state or local laws.

It is unlawful in Massachusetts to require or administer a lie detector test as a condition of employment or continued employment. Pursuant to the San Francisco Fair Chance Ordinance, we will consider qualified applicants with arrest and conviction records for employment.

We may use artificial intelligence (AI) tools to support parts of the hiring process, such as reviewing applications, analyzing resumes, or assessing responses. These tools assist our recruitment team but do not replace human judgment. Final hiring decisions are ultimately made by humans.