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 in Automated Driving, Energy & Materials, Human-Centered AI, Human Interactive Driving, Large Behavioral Models, and Robotics.
The Automated Driving Advanced Development division at TRI will focus on enabling innovation and transformation at Toyota by building a bridge between TRI research and Toyota products, services, and needs. We achieve this through partnership, collaboration, and shared commitment. This new division is leading a new cross-organizational project between TRI and Woven by Toyota to conduct research and develop a fully end-to-end learned driving stack. This cross-org collaborative project is harmonious with TRI’s robotics divisions' efforts in Diffusion Policy and Large Behavior Models.
We are looking for a Software Engineer to join our growing team and contribute to the integration and deployment of our automated driving stack on real-world vehicles. As a generalist engineer, you will work across the autonomy system, helping implement features, set up infrastructure, and improve the performance and robustness of our real-time autonomy stack. You’ll work alongside senior engineers and researchers across TRI and Woven, gaining exposure to multiple parts of the system while deepening your expertise in modern robotics and vehicle software.
This role is ideal for an engineer with a strong foundation in C++ and Python, an interest in real-world systems, and a desire to grow in a fast-paced, collaborative environment. You'll partner closely with end-to-end machine learning, simulation and infrastructure teams to ensure that the full stack runs robustly on real vehicles in closed-course, public road and simulation testing.
This work is part of Toyota’s global AI efforts and will be conducted in close collaboration with teams across TRI, Woven by Toyota, and other engineering partners.
Please include links to any relevant open-source contributions or technical project write-ups with your application.
The pay range for this position at commencement of employment is expected to be between $152,000 and $228,000/year for California-based roles; however, base pay offered may vary depending on multiple individualized factors, including market location, job-related knowledge, skills, and experience. Note that TRI offers a generous benefits package (including 401(k) eligibility and various paid time off benefits, such as vacation, sick time, and parental leave) and an annual cash bonus structure. Details of participation in these benefit plans will be provided if an employee receives an offer of employment.
Please reference this Candidate Privacy Notice to inform you of the categories of personal information that we collect from individuals who inquire about and/or apply to work for Toyota Research Institute, Inc. or its subsidiaries, including Toyota A.I. Ventures GP, L.P., and the purposes for which we use such personal information.
TRI is fueled by a diverse and inclusive community of people with unique backgrounds, education and life experiences. We are dedicated to fostering an innovative and collaborative environment by living the values that are an essential part of our culture. We believe diversity makes us stronger and are proud to provide Equal Employment Opportunity for all, without regard to an applicant’s race, color, creed, gender, gender identity or expression, sexual orientation, national origin, age, physical or mental disability, medical condition, religion, marital status, genetic information, veteran status, or any other status protected under federal, state or local laws.
It is unlawful in Massachusetts to require or administer a lie detector test as a condition of employment or continued employment. An employer who violates this law shall be subject to criminal penalties and civil liability. Pursuant to the San Francisco Fair Chance Ordinance, we will consider qualified applicants with arrest and conviction records for employment.
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