Human-Aware Robot Learning Intern

Toyota Research Institute Inc.; Cambridge (MA); Hybrid; USD 55,000 - 80,000; Part time

Benefits offered by this job

Medical, dental, and vision insurance

Paid time off including holidays and S

Job summary

Toyota Research Institute (TRI) seeks a research intern for the Human Aware Interaction and Learning (HAIL) team in Massachusetts. The role emphasizes developing data-efficient robot learning methods, collaborating with humans, and prototyping software on real hardware.

You will run experiments, build prototypes, and contribute toward publishable findings while helping to expand a new corpus of robot data and insights from large-scale datasets.

Qualifications

• Pursuing a degree (Ph.D., M.S.) in Robotics, Computer Science, Mechanical Engineering, or related field.
• Publication record in robotics/ML conferences is desirable.
• Hardware experience and deployment of learned policies on real robots is preferred.
• Strong ML background and familiarity with large datasets and benchmarks.
• Proficiency in Python; C++ skills are helpful but not required.

Responsibilities

• Create working code prototypes and run experiments in simulation and on real robots.
• Interact with team members and contribute to publishable research.
• Help build and maintain a corpus of robot data and conduct user studies where applicable.
• Support data-efficient and robust learning for multimodal policies with human interaction.

Skills

Python programming

ML experience

Robotics hardware

C++ (helpful)

User studies

Proactive mindset

Passion for robotics

Education

Ph.D./M.S. in Robotics, Computer Science, Mechanical Engineering, or related

Tools

Python

C++

Job description

Toyota Research Institute (TRI) seeks a research intern for the Human Aware Interaction and Learning (HAIL) team in Massachusetts. The role emphasizes developing data-efficient robot learning methods, collaborating with humans, and prototyping software on real hardware.

You will run experiments, build prototypes, and contribute toward publishable findings while helping to expand a new corpus of robot data and insights from large-scale datasets.