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.
Our Human-Aware Interaction and Learning team is looking for Research Scientists with experience in machine learning relating to fields such as Reinforcement Learning, Shared Control, Computer Vision, Language-based models, and Human-Machine Interaction.
As a Research Scientist, you will work with a multidisciplinary team proposing, conducting, and transferring innovative research in Machine Learning for human-centric applications.
You will use large amounts of real-world and simulated sensory data to solve open problems, publish at top academic venues, and test your ideas in the real world (including our innovative motion simulators, test vehicles, and robots).
You will help to transfer and ship our most successful algorithms and models towards real-world advanced assistance systems, touching millions of lives.
Requirements
Conduct ambitious research on large-scale computational behavior models that enable shared autonomy and human-machine interactions on the road – Human-Centric ML that solves open problems of high practical value, validating the approaches in real-world benchmarks and systems.
Push the boundaries of knowledge and the state of the art in Human-Machine Interaction and Shared Control in driving and robotics contexts.
Partner with a multidisciplinary team including other research scientists and engineers across the Human Interactive Driving team, TRI, Toyota, and our university partners.
Stay up to date on the state-of-the-art in Machine Learning ideas and software.
Present results in verbal and written communications, internally, at top international venues, and via open source contributions to the community.
Lead collaborations with our external research partners (e.g., MIT, Stanford, UMich) and mentor research interns.
Create ambitious new technologies in the space of interaction learning, interactive machine learning, imitation/reinforcement learning, and large-scale models.
Bachelor’s or Master’s degree in a quantitative field with 5 years of experience (e.g. Computer Science, Mathematics, Physics, Engineering, Chemistry) or Ph.D. or deep expertise in one key area (Machine Learning, Robotics, Computer Vision, Human-Machine Interaction, Human Behavior Modeling) or related fields that leverage ML for understanding and interacting with humans.
Consistent track record of publishing at high-impact conferences/journals (CVPR, ICLR, NeurIPS, ICML, CoRL, RSS, ICRA, ICCV, ECCV, PAMI, IJCV, etc.) Experience with ML and use of scientific Python, Unix, and a common DL framework (preferably PyTorch). Experience with distributed learning (especially on AWS) is a plus.
Experience with ML work on LLMs and/or other large-scale models. Experience with task-learning (imitation or reinforcement learning) is a plus.
You can collaborate with other researchers and engineers to complete new ML projects, from initial idea to working solution and publication.
You are passionate about developing and applying human-centric artificial intelligence for societal good.
You are a reliable team player and like to think big and go deeper.
You care about openness and delivering with integrity.
Benefits
Please add a link to Google Scholar and include a full list of publications when submitting your CV to this position.
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.
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