Machine Learning Research Scientist, Adaptive Behavioral Systems

Job Description

Job Description

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

Responsibilities

• 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.

Qualifications

• 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.

Bonus Qualifications

• 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).

Please add a link to Google Scholar to include a full list of publications when submitting your CV for this position.

 

The pay range for this position at commencement of employment is expected to be between $176,000 and $253,500/year for California-based roles. Base pay offered will depend on multiple individualized factors, including, but not limited to, a candidate's experience, skills, job-related knowledge, and market location. 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.

 

Please reference this Candidate Privacy Notice to inform you of the categories of personal information that we collect from individuals who inquire about and/or apply to work for Toyota Research Institute, Inc. or its subsidiaries, including Toyota A.I. Ventures GP, L.P., and the purposes for which we use such personal information.

 

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, without regard to an applicant’s race, color, creed, gender, gender identity or expression, sexual orientation, national origin, age, physical or mental disability, medical condition, religion, marital status, genetic information, veteran status, or any other status protected under federal, state or local laws.

 

It is unlawful in Massachusetts to require or administer a lie detector test as a condition of employment or continued employment. An employer who violates this law shall be subject to criminal penalties and civil liability. Pursuant to the San Francisco Fair Chance Ordinance, we will consider qualified applicants with arrest and conviction records for employment.

We may use artificial intelligence (AI) tools to support parts of the hiring process, such as reviewing applications, analyzing resumes, or assessing responses. These tools assist our recruitment team but do not replace human judgment. Final hiring decisions are ultimately made by humans. If you would like more information about how your data is processed, please contact us.