Part-Time Student Worker Automation & Behavioral Science Engineer - Zoox

About Zoox

Zoox is transforming mobility with fully autonomous, electric vehicles designed from the ground up for a driverless future. Our mission is to make transportation safer, more sustainable, and accessible to everyone. At Zoox, innovation, collaboration, and a bold vision for the future drive everything we do.

About Our Part Time Student Worker Program

Zoox’s program offers hands-on experience with cutting-edge technology, mentorship from some of the industry’s brightest minds, and the opportunity to make meaningful contributions to real projects. We seek part time student workers who demonstrate strong academic performance, engagement beyond the classroom, intellectual curiosity, and a genuine interest in Zoox’s mission.

Zoox is seeking a motivated (graduate or upper-level undergraduate) student worker to join our team, focusing on (building and validating a driving risk assessment system, an experimental RAG system for proactively testing autonomous-vehicle behavior)

In this role, you will:

Design, build, and iterate on an end-to-end RAG pipeline for autonomy validation, owning it from prototype to demo

Define and run empirical experiments that "show it with data" rather than relying on assumptions

Work through ambiguous, open-ended problems with a researcher's mindset and a bias toward rapid iteration

Communicate complex results, trade-offs, and uncertainty clearly to the team and stakeholders

Currently pursuing a B.S. or M.S. in a relevant quantitative field (Engineering, CS, Physics, Neuroscience, Biology/Computational Bio, or similar)

Strong programming skills in Python

Solid data manipulation understanding (e.g., SQL, Pyspark, Scala)

Solid foundation in machine learning and statistics

Comfort operating independently under high uncertainty on open-ended problems

Excellent written and verbal communication; able to convey complexity and ambiguity clearly

Strong teamwork and collaboration skills

Experience with RAG systems, LLMs, or vision-language models (VLMs)

Background in a quantitative discipline (Neuroscience, Physics, Computational Bio, etc.)

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 pursuing a B.S. or M.S., in a relevant engineering field.

Available for a 6 month project

Able to commit to at least 40 hours per week

Ability to commute on-site to Foster City

Student Worker may not use proprietary Zoox information in university theses, publications, or share it outside.