Machine Learning Research Scientist, Adaptive Behavioral Systems

• Conduct machine learning research that integrates behavioral science concepts to push the boundaries of knowledge and the state of the art in Human-Centered AI. • Develop and evaluate generative AI and machine learning methods for modeling and understanding human behavior. • Collaborate cross-functionally with researchers in multiple fields, as well as university partners. • Stay up to date on the state-of-the-art in machine learning theories, methods and tooling. • Collaborate with scientists in the Adaptive Behavioral Systems Department to shape our research program and to communicate research to Toyota stakeholders. • Publish research findings in academic journals and/or conferences. • Contribute to technology transfer of research insights and prototypes throughout Toyota.

• PhD in computer science, machine learning, or a closely related field with 1-7 years of experience in machine learning research or related projects in an industry setting, particularly in areas related to LLM training or large-scale ML. Industry experience is a plus. • A strong publication record in ML, NLP, deep learning, or related fields. • Awareness of current machine learning research and the ability to critically evaluate emerging techniques and literature. • Experience with LLM/MLLM pretraining, fine-tuning (e.g., SFT, RLHF) and agentic systems. • Proficiency in Python and modern deep learning frameworks such as Pytorch or Tensorflow • Ability to work collaboratively across disciplines and functions. • Ability to balance multiple projects, including short-term and those that may span several years. • Strong project management skills and desire to work on cutting-edge open-ended research projects. • Demonstrated ability to independently identify research opportunities, formulate well-scoped problems, and lead research projects end-to-end. • Demonstrated ability to work autonomously while soliciting feedback. • Strong interpersonal skills. Great teammate. • Experience with one or more of the following areas: diffusion models, uncertainty modeling, reinforcement learning, and physiological signal processing. • Previous experience in human modeling (both cognitive and behavioral) with generative AI. • Experience with human-centered research (e.g. computational behavioral and social science, human-computer interaction, neuro-science).