Human Interactive Driving Intern, Platform Research Systems Integration

Team: Internships - Summer 2027

Location: Los Altos, CA

Commitment: Intern

Workplace Type: hybrid

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.

This is a paid 12-week internship opportunity and is a hybrid, in-office role.

Here’s a glimpse into the Internship experience from some of our TRI interns!

Responsibilities

Contribute to the design and integration of an AI monitoring system for custom vehicle platforms.
Explore how new data modalities such as audio and video fit into the vehicle monitoring system alongside CAN data.
Deploy and run monitoring and AI models on in-vehicle edge computers.
Assist in the design and integration of hardware and software systems.
Collaborate with our multidisciplinary teams to learn and address integration challenges.
Document integration processes, procedures, and outcomes for future reference and improvement.
Contribute to the continuous enhancement of our integration processes and methodologies.
Proactively engage in self-improvement and skill development, staying updated with the latest technologies and industry best practices.
Approach tasks with enthusiasm and a commitment to achieving project objectives while fostering a positive and collaborative attitude.
Communicate effectively with team members and other departments, promoting an open-minded and cooperative work environment.

Qualifications

Currently pursuing a Master degree in Mechanical Engineering, Electrical Engineering, Computer Science, Robotics, or a related field.
A strong interest in gaining experience in the integration of mechanical, electrical, and software systems.
Proficiency in Python, including experience with data analysis libraries (NumPy, pandas) and writing tested code.
Experience with embedded Linux and edge AI hardware, ideally NVIDIA Jetson (JetPack, CUDA, TensorRT/ONNX Runtime, Docker on ARM64).
Familiarity with C++, MATLAB/SIMULINK, Network (Ethernet/CAN).
Experience working with CAD is preferred.
Demonstrated self-motivation and a strong desire for continuous learning and skill development.
An eager and humble attitude with a commitment to contributing to project goals.
An open-minded and adaptable approach to problem-solving.
Good communication skills with the ability to work effectively within cross-functional teams.
Strong problem-solving and troubleshooting aptitude.

Bonus Qualifications

Coursework or project experience in machine learning and/or building with LLMs (prompting, tool/function calling, evaluation).
Optimizing models for edge inference (quantization, TensorRT, DeepStream).
Knowledge of ROS or other relevant programming skills.
Familiarity with the safety-critical system design process (FMEA, FTA).