Toyota Research Institute
Machine Learning Researcher, Carbon Neutrality
📍
Los Altos, CA
🧪
Mid-Senior level
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 Robotics, Human-Centered AI, Human Interactive Driving, and Energy & Materials.
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.
We are looking for a Machine Learning Researcher with expertise and passion for foundation models, as well as training and fine-tuning on large, industrial-scale datasets. This researcher would work to define new lines of research in the generative AI space in relation to training and fine-tuning models representing human behaviors and cognitive processes, such as changes in beliefs and preferences over time. This researcher may also apply data science expertise to inform carbon neutral policy and strategy decisions.
Responsibilities
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.
Pursuant to the San Francisco Fair Chance Ordinance, we will consider qualified applicants with arrest and conviction records for employment.
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.
We are looking for a Machine Learning Researcher with expertise and passion for foundation models, as well as training and fine-tuning on large, industrial-scale datasets. This researcher would work to define new lines of research in the generative AI space in relation to training and fine-tuning models representing human behaviors and cognitive processes, such as changes in beliefs and preferences over time. This researcher may also apply data science expertise to inform carbon neutral policy and strategy decisions.
Responsibilities
- Conduct daring research, primarily in the area of generative AI models, that solves open problems of high practical and/or ethical value and validate it in real-world benchmarks and systems
- Push the boundaries of knowledge and the state of the art in Human-Centered AI, including: NLP, multi-modal models, and time-varying language models
- Stay up to date on the state-of-the-art in Machine Learning theories, practice, and software
- Conduct exploratory analyses with large datasets to identify areas of opportunity and address strategic questions
- Collaborate with scientists in the Carbon Neutrality Department to craft and shape our research program and to communicate research to Toyota partners
- Publish findings in academic journals and/or conferences
- Contribute to technology transfer of research throughout Toyota
- PhD in natural language processing, computer vision, machine learning, or related field
- 3+ years of experience in machine learning research or related projects
- Experience with generative AI models
- Broad knowledge of machine learning approaches and theory
- Capable of working collaboratively across subject areas and functions
- Desire to work on challenging open-ended research projects
- Demonstrated ability to work autonomously while soliciting feedback
- Strong interpersonal skills and an excellent teammate
- Strong data science skills. Proficiency in R and/or Python
- Proficiency in other big data languages and tools for cloud environments (e.g., Databricks, SQL, PySpark)
- Ability to communicate sophisticated concepts clearly across different audiences
- Please include a link to your Google Scholar page
- Experience with language transformers, vision transformers, diffusion models, or multi-modal models
- Ability to balance multiple projects, including short-term, targeted analyses and novel, innovative projects that may span years
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.
Pursuant to the San Francisco Fair Chance Ordinance, we will consider qualified applicants with arrest and conviction records for employment.