Human Interactive Driving Intern, Platform Research Systems Integration

Toyota Research Institute•Los Altos, CA

5d•Hybrid

About The Position

Toyota Research Institute (TRI) is seeking a System Integration Engineering Intern for its Platform Research team within the Human Interactive Driving division. The team develops advanced research platforms to improve vehicle system design and integrate hardware and software, with a focus on a “Software First” approach, unified hardware architectures, rapid prototyping, and iterative testing. The intern will work with multidisciplinary teams on engineering projects from concept through execution, helping envision, design, and develop research platforms. This is a paid, 12-week, hybrid, in-office internship. The role offers hands-on experience with emerging technologies, cross-functional collaboration, mentorship, networking, and professional development.

Requirements

Currently pursuing a master’s degree in Mechanical Engineering, Electrical Engineering, Computer Science, Robotics, or a related field.
Strong interest in gaining experience integrating mechanical, electrical, and software systems.
Proficiency in Python, including data analysis libraries such as NumPy and pandas, and experience writing tested code.
Experience with embedded Linux and edge AI hardware.
Demonstrated self-motivation and desire for continuous learning and skill development.
Eager and humble attitude, with commitment to contributing to project goals.
Open-minded and adaptable approach to problem-solving.
Good communication skills and ability to work effectively in cross-functional teams.
Strong problem-solving and troubleshooting aptitude.

Nice To Haves

Experience with NVIDIA Jetson, including JetPack, CUDA, TensorRT or ONNX Runtime, and Docker on ARM64.
Familiarity with C++, MATLAB/SIMULINK, and Ethernet or CAN networking.
Experience working with CAD.
Coursework or project experience in machine learning and/or building with LLMs, including prompting, tool/function calling, or evaluation.
Experience optimizing models for edge inference, including quantization, TensorRT, or DeepStream.
Knowledge of ROS or other relevant programming skills.
Familiarity with safety-critical system design processes such as FMEA and FTA.

Responsibilities

Contribute to the design and integration of an AI monitoring system for custom vehicle platforms.
Explore how audio and video data can be incorporated into vehicle monitoring systems 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 multidisciplinary teams to learn about and address integration challenges.
Document integration processes, procedures, and outcomes for future reference and improvement.
Contribute to the continuous improvement of integration processes and methodologies.
Pursue ongoing self-improvement and skill development, keeping up with current technologies and industry practices.
Approach tasks enthusiastically and work toward project objectives while maintaining a positive, collaborative attitude.
Communicate effectively with team members and other departments, supporting an open-minded and cooperative work environment.