Contract Student Worker - Autonomy Safety Data Engineer

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.

Key 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.

Additional information

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.

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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.

• 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.

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