Zoox's part-time student worker program puts you at the center of one of the most ambitious challenges in transportation. You'll contribute to real projects, work alongside engineers and researchers pushing the boundaries of autonomous technology, and gain experience that goes well beyond the classroom. We're looking for students who bring strong academic foundations, curiosity that doesn't stop at coursework, and a drive to be part of something that matters.
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.
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
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
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
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.
We want to be transparent: this is not an internship. The Contract Student Worker Program is designed to complement your academic experience by providing meaningful, ongoing work alongside your studies. Rather than participating in a cohort-based program, you'll join a team directly and contribute to real projects with real impact. While the program does not include structured intern programming or a pathway to full-time employment, it offers valuable opportunities to learn, develop new skills, and gain hands-on experience in a professional environment.
Compensation for this role is $30/hour.
This is a contract position; employment will be through a vendor contracted with Zoox. The hourly rate is as posted, and benefits eligibility is determined by the vendor.
About Zoox
Zoox is developing the first ground-up, fully autonomous vehicle fleet and the supporting ecosystem required to bring this technology to market. Sitting at the intersection of robotics, machine learning, and design, Zoox aims to provide the next generation of mobility-as-a-service in urban environments. We’re looking for top talent that shares our passion and wants to be part of a fast-moving and highly execution-oriented team.
Accommodations
If you need an accommodation to participate in the application or interview process please reach out to accommodations@zoox.com or your assigned recruiter.
A Final Note:
You do not need to match every listed expectation to apply for this position. Here at Zoox, we know that diverse perspectives foster the innovation we need to be successful, and we are committed to building a team that encompasses a variety of backgrounds, experiences, and skills.
