Human Interactive Driving Intern, Platform Research Systems Integration

At Toyota Research Institute (TRI), we're on a mission to improve the quality of human life. TRI is seeking System Integration Engineering Interns to play a key role in envisioning, designing, and developing cutting-edge research platforms within the Platform Research team, part of the Human Interactive Driving (HID) division. This is a paid 12-week internship opportunity and is a hybrid, in-office role.

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 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 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

Requirements

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); 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

Nice to have

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); Experience working with CAD is preferred

Benefits

Paid 12-week internship; Generous benefits package; Medical, dental, and vision insurance; Paid time off benefits (including holiday pay and sick time); Access to networking, mentorship, and development resources