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.
About the Team
This role sits within the Carbon Neutral Strategy (CNS) team in the Energy and Materials (E&M) division. CNS operates at the intersection of technology, business, and policy to inform decarbonization and circularity strategy across the Toyota ecosystem.
We combine energy systems modeling, machine learning, and real-world data to inform decisions around vehicle circularity, electrification and EV adoption, energy infrastructure and grid interaction, and policy analysis. While based in the U.S., our scope is global. We collaborate closely with TRI researchers across robotics, materials science, and behavioral science, as well as Toyota business leaders, policy teams, and external research partners.
The Opportunity
We are looking for a Data Engineer to design and build the data systems that power advanced analytics, forecasting, and AI-driven research across CNS. You will define how data flows through the team, from fragmented sources to reliable datasets used in predictive modeling, scenario analysis, and LLM-enabled workflows. This role requires balancing strong engineering fundamentals with the flexibility to support rapid research iteration in a fast-evolving AI and sustainability landscape.
You will partner with ML researchers, technical leads, and research scientists at TRI to translate evolving research needs into robust data systems. You will also collaborate with Toyota partners on data access, governance, and use.
Responsibilities
Design, implement, and maintain data pipelines to ingest structured, semi-structured, and unstructured data.
Develop data models that support predictive modeling, scenario analysis, and LLM-based workflows.
Improve data tooling and automation to enable rapid prototyping and iteration.
Integrate third-party APIs, domain-specific datasets, and global data sources.
Establish standards for data quality, lineage, governance, and reproducibility.
Participate in exploratory data analysis to validate assumptions, identify data gaps, surface insights and improve model inputs.
Collaborate with internal and external partners on secure data access and governance.
Qualifications
Bachelor’s degree in a quantitative field (e.g. engineering, computer science, data science, or a related discipline).
Background in analytics, experimentation, or statistical analysis.
3-5 years of experience in data engineering or software engineering with a strong data focus.
Proven track record of designing and implementing pipelines across heterogeneous data sources.
Ability to validate ideas through fast experimentation and iterative prototyping.
Strong proficiency in Python, SQL, Unix tooling, and Git-based workflows.
Experience working with structured and unstructured data.
Experience with cloud services (preferably AWS and Databricks).
Experience integrating external APIs and third-party datasets.
Strong communication skills and ability to collaborate across technical and business teams.
Experience with enterprise big data.
Familiarity with ETL frameworks and data warehousing concepts.
Bonus Qualifications
Experience with automotive, manufacturing, mobility, or energy systems data.
Experience in AI/ML model development, including LLM-driven or generative/agentic AI workflows.
The pay range for this position at commencement of employment is expected to be between $144,000 and $207,000/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.
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