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 Team
TRI’s Carbon Neutrality Department within our Human-Centered AI (HCAI) Division blends behavioral science, human-computer interaction research, and machine learning to understand, predict and enable carbon neutral behavior.
The Opportunity
We are looking for an AI research scientist who has expertise in and ethusiasm for machine learning research (e.g. foundation models, including training and fine-tuning on large, industrial-scale datasets). This researcher would work at the intersection of social science and generative AI, training and fine-tuning models representing human behaviors and cognitive processes, such as changes in beliefs and preferences over time. For an example of our research in this vein, please see https://arxiv.org/abs/2403.20252
Responsibilities
Collaborate cross-functionally with specialists in multiple fields, as well as university partners, to research and develop technology that employs and leverage generative AI to understand human behavior and preferences.
Conduct research that integrates behavioral and social science concepts with machine learning methods to push the boundaries of knowledge and the state of the art in Human-Centered AI.
Stay up to date on the state-of-the-art in Machine Learning theories, practice, and software.
Collaborate with scientists in the Carbon Neutrality Department to shape our research program and to communicate research to Toyota collaborators.
Publish findings in academic journals and/or conferences.
Contribute to technology transfer of research throughout Toyota.
Qualifications
PhD or equivalent experience in computer science, machine learning, social science computation, or related field.
3+ years of experience engaged in research pertaining to machine learning or related projects in an industry setting.
Experience with LLM/MLLM, large scale fine-tuning (e.g., SFT, RLHF), RAG and agentic systems.
Experience in human-centered research (e.g. behavioral data science, computational social science, human-computer interaction), including qualitative and/or quantitative methods such as experiments and user studies.
Experience with Python, C++, C, Java, or other related language deep learning frameworks such as Pytorch or Tensorflow.
Broad knowledge of machine learning approaches and theory.
Ability to balance multiple projects, including short-term, targeted analyses and novel, cutting-edge projects that may span several years.
Ability to work collaboratively across subject areas and functions.
Strong project management skills and desire to work on challenging open-ended research projects.
Evidenced skill in operating autonomously while seeking feedback.
Strong interpersonal skills and great teammate.
Ability to communicate complex concepts clearly across different audiences.
Bonus Qualifications
Experience with one or more of the following areas: diffusion models, uncertainty modeling, reinforcement learning, physiological signal processing, time series modeling, and data analysis.
Previous experience in human modeling (both cognitive and behavioral) with generative AI.
The pay range for this position at commencement of employment is expected to be between $200,000 and $300,000/year for California-based roles. Base pay offered will depend on multiple individualized factors, including, but not limited to, business or organizational needs, market location, job-related knowledge, skills, and experience. TRI offers a generous benefits package including medical, dental, and vision insurance, 401(k) eligibility, paid time off benefits (including vacation, sick time, and parental leave), and an annual cash bonus structure. Additional details regarding these benefit plans will be provided if an employee receives an offer of employment.
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