Tri5mo ago

Machine Learning Research Scientist, Adaptive Behavioral Systems

Los AltosFull-timemid

Data ScienceMachine LearningData & AI

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Quick Summary

Overview

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.

Technical Tools

Data ScienceMachine LearningData & AI

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 advancing the state of the art in AI, robotics, driving, and material sciences.

The Team

TRI’s Adaptive Behavioral Systems Department within our Human-Centered AI (HCAI) Division aims to develop AI systems that can support behavior change, such as reducing carbon emissions. To do this, we are developing novel models of human behavior that integrate behavioral science, Human-Computer Interaction, and advanced machine learning.

The Opportunity

We are looking for an AI Research Scientist, or Senior Machine Learning Research Scientist with expertise in large-scale foundational model training, fine-tuning, evaluation and benchmarking. This role operates at the forefront of generative machine learning and human behavior modeling. Ideal candidates will bring a strong research track record, hands-on experimentation skills, and experience developing and deploying foundational models. This role sits at the intersection of social science and generative AI, building models that represent human beliefs, preferences, and cognition as they change over time. For an example of our early research in this vein, please see https://arxiv.org/abs/2403.20252.

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).