Toyota Research Institute

At Toyota Research Institute (TRI), we’re working to build a future where everyone has the freedom to move, engage, and explore. Join us in our mission to improve the quality of human life through advances in artificial intelligence, automated driving, robotics, and materials science. We’re dedicated to building a world of “mobility for all” where everyone, regardless of age or ability, can live in harmony with technology to enjoy a better life, through innovations in AI and robots.

Our work is guided by a dedication to safety – in both what we research and how we perform our research, our goal is to benefit society. As a subsidiary of Toyota, TRI is fueled by a diverse and inclusive community of people who bring invaluable leadership, experience, and ideas from leading industry and academic institutions. We are actively involved with the broader academic community and promote the sharing of research outcomes through publications, funding, and open-source software. We’re continually searching for the world’s best talent ‒ people who are ready to define the new world of mobility with us!

We’re building a company helping people to thrive, achieve work-life balance, and bring their best selves to work. At TRI, you will have the opportunity to enjoy the best of both worlds ‒ a fun environment with forward-thinking people who enjoy solving tough problems and the financial backing to successfully achieve your goals. Come work with TRI to enable the elderly to age in place. Start your impossible with us.

Our team melds complementary research and engineering expertise in soft robotics, physical human-robot interaction, humanoid systems, software development, education, entertainment, consumer electronics, and user-centered design. We are developing human-centered hardware and algorithms for putting highly compliant, sensing robotic systems to work in the domestic setting, and innovating manipulation skills that physically support and amplify older adults and ensure continued independent living.

TRI has the runway, roadmap, and expertise to transition the technology development to a product that impacts the lives of millions of people. Join a fast-moving team that demands high-risk innovation and learning from failures, using rigorous processes to identify key technologies, develop a robust, high-quality system, and quantitatively evaluate performance. As part of the team, you will be surrounded and supported by the significant core ML, cloud, software, and hardware expertise at TRI, and be a part of TRI’s positive and diverse culture.

Responsibilities:
Develop, integrate, and deploy algorithms for motion planning and control in highly cluttered spaces, planning for rich-contact tasks and dexterous manipulation
Develop and integrate control algorithms that exploit tactile feedback and multi-modal sensing in constrained domestic environments
Invent and deploy innovative solutions at the intersection of machine learning, soft-robotics, tactile sensing, manipulation, human interaction, and simulation for performing useful, human-level tasks, in and around homes
Co-invent novel ways to engineer and learn robust, real-world behaviors, incorporating optimization, planning, reactive control, self-supervision, active learning, learning from demonstration, simulation and transfer learning, and real-world adaptation, etc.
Work closely with Human-Robot Interaction researchers in understanding human needs and applications
Follow best practices producing maintainable code, including automated testing, continuous integration, code style conformity, and code review

Qualifications:
M.S. or Ph.D. in an relevant technical field OR equivalent industry experience
A strong background with motion planning methods, specifically contact-aware planning methods, for multi-DoF dexterous manipulation in cluttered and constrained environments
Strong software engineering skills, preferably in C++ and Python, and in analysis and debugging of autonomous robotic systems
A standout colleague with strong communication skills, and an ability to learn from others and contribute back to the robotics community with publications or open source code
Passionate about assisting and amplifying older adults and those in need through domestic human-robot collaboration and physical assistance innovation

Additional experience or knowledge in any of the following areas:
Reactive planning and control, coordinated whole-body control, dexterous manipulation, grasp planning, and human interaction
Application of machine learning to robotics, including reinforcement, imitation, and transfer learning
Tactile sensing, modeling soft-contact, and in soft robotics
Integration of multi-modal sensing into planning and control and in development of sensor fusion methods
Mobile and/or legged locomotion in constrained environments

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