Improving the quality of human life through advances in automated driving, energy and materials, robotics, and AI.
About the Company
Toyota Research Institute (TRI) is dedicated to advancing human life through cutting-edge research and innovation. With a focus on Automated Driving, Energy & Materials, Human-Centered AI, Human Interactive Driving, Large Behavior Models, and Robotics, TRI develops transformative technologies to enhance mobility and amplify human potential. The institute brings together world-class talent to bridge scientific research with real-world applications, driving the future of intelligent systems.
About the Role
This position is part of TRI’s Human Interactive Driving team, working on the groundbreaking “Mobility 3.0” project. The initiative seeks to connect advanced research with product development, focusing on novel applications of AI and computer vision for diverse vehicle platforms, including small-scale and experimental designs. The role involves close collaboration with partners in Japan, rapid prototyping, and deployment of innovative mobility solutions.
Responsibilities
- Collaborate with cross-functional teams to generate concepts for computer vision applications, assessing their feasibility and data requirements.
- Partner with mechanical, electrical, and software engineers to design and implement testing strategies for computer vision within mechatronic systems.
- Lead the design, development, and deployment of computer vision systems for unique vehicle platforms.
- Participate in testing of experimental vehicles, with occasional travel to California and Japan.
Required Skills
- Master’s degree in Computer Science or a related field, or a Bachelor’s degree with 3–5 years of relevant experience.
- Proven expertise in fine-tuning, training, and deploying machine learning-based computer vision systems.
- Solid understanding of current state-of-the-art methods in computer vision.
Preferred Qualifications
- Hands-on experience with hardware integration, particularly robotics with camera systems.
- Familiarity with machine learning infrastructure and tools.