Human Interactive Driving Intern, Platform Research Systems Integration

Toyota Research Institute•Los Altos, CA

7d•$45 - $65•Hybrid

About The Position

Toyota Research Institute (TRI) is hiring a paid, 12-week intern for its Platform Research team within the Human Interactive Driving division. This hybrid, in-office position contributes to the design and development of research platforms that integrate vehicle hardware and software. The team pursues a “Software First” approach using unified hardware architectures and streamlined integration processes to enable rapid prototyping and iterative testing, with the goal of advancing safer and more enjoyable driving experiences. The intern will work with multidisciplinary teams on engineering projects throughout development, from concept through execution. The role focuses on integrating an AI monitoring system for custom vehicle platforms, exploring audio and video alongside CAN data, and deploying monitoring and AI models on in-vehicle edge computers. TRI offers hands-on experience with emerging technologies, cross-functional collaboration, mentorship, networking, and professional development. The expected base pay at commencement is $45–$65 per hour for California-based roles. Actual pay depends on individualized factors including experience, skills, job-related knowledge, and market location. TRI offers medical, dental, and vision insurance, plus paid time off including holiday pay and sick time. Additional benefits details are provided if an employee receives an offer.

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 experience with data analysis libraries such as NumPy and pandas, and writing tested code.
Experience with embedded Linux and edge AI hardware; NVIDIA Jetson experience is preferred, including JetPack, CUDA, TensorRT/ONNX Runtime, or Docker on ARM64.
Familiarity with C++, MATLAB/SIMULINK, and networking such as Ethernet/CAN.
Self-motivation and a strong desire for continuous learning and skill development.
Eager and humble attitude and commitment to contributing to project goals.
Open-minded and adaptable approach to problem-solving.
Good communication skills and ability to work effectively within cross-functional teams.
Strong problem-solving and troubleshooting aptitude.

Nice To Haves

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, such as 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 modalities can be incorporated into vehicle monitoring alongside CAN data.
Deploy and run monitoring and AI models on in-vehicle edge computers.
Assist with 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 skill development and stay current with technologies and industry practices.
Approach tasks enthusiastically and work toward project objectives while fostering a positive, collaborative attitude.
Communicate effectively with team members and other departments to promote an open-minded, cooperative work environment.