Description
Role Overview
This role focuses on building a data-driven safety risk model that quantifies and improves autonomous-vehicle driving performance, along with the data analysis work that supports it. The student will work within the Safety Strategy & Operations team on a 6-month project spanning model development, empirical experimentation, and large-scale driving/simulation data analysis.
Responsibilities
- Support designing, building, and iterating on a data-driven safety risk model that quantifies driving performance and surfaces safety-relevant signals across the autonomy stack
- Assist developing and maintaining dataset management pipelines — curation, labeling, versioning, and quality checks — that feed the risk model and downstream analyses
- Support defining and running empirical experiments that “show it with data” rather than relying on assumptions
Required Qualifications
- Assist analyzing large-scale driving and simulation datasets to identify trends, edge cases, and opportunities to improve autonomy performance
- Currently pursuing a B.S. or M.S. in a relevant quantitative field (Engineering, Computer Science, Statistics, Physics, or similar)
- Strong programming skills in Python
- Help work through ambiguous, open-ended problems with a researcher’s mindset and a bias toward rapid iteration
- Solid data manipulation understanding (e.g., SQL, PySpark, Scala)
- Solid foundation in statistics, machine learning, and risk or reliability modeling
- Help communicate complex results, trade-offs, and uncertainty clearly to the team and stakeholders
- Comfort operating independently under high uncertainty on open-ended problems
Bonus Qualifications
- Excellent written and verbal communication; able to convey complexity and ambiguity clearly
- Experience with safety, reliability, or risk modeling (e.g., survival analysis, Bayesian methods, causal inference)
- Experience with large-scale dataset management, data pipelines, or MLOps tooling
- Strong teamwork and collaboration skills
- Background in autonomous vehicles, robotics, or a related quantitative discipline
- Prior research experience taking ambiguous, end-to-end problems from zero to a result, independently
Program Requirements
- Genuine interest in autonomous vehicles and Zoox’s mission
- Currently enrolled in a B.S. or M.S. program in a relevant discipline.
- Available to commit to a minimum three-month assignment.
- Able to commit a minimum of 20 hours per week.
- Able to work on-site at one of our office locations.
- Must adhere with Zoox confidentiality requirements, including refraining from using or sharing proprietary company information outside of Zoox, such as in academic research, theses, publications, or presentations.
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