Toyota Research Institute (TRI) is looking to improve the quality of human life by developing new tools and capabilities to amplify the human experience, specifically in the area of human-centric artificial intelligence for mobility and interaction with humans.
Requirements
- 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.
- Background in 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.).
- Familiarity with Reinforcement Learning, Shared Control, Computer Vision, Language-based models, and Human-Machine Interaction.
Responsibilities
- 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.
Other
- 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.
- 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.
- Ability to collaborate with other researchers and engineers to complete new ML projects, from initial idea to working solution and publication.
