The board
Job
Engineering
Contract Student Worker Automation & Behavioral Science Engineer
Zoox · Software
- Hours
- Contract
- Where
- Foster City, CA
- Posted
- Jun 4
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.
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.
Project Overview
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 sy…
What you'd do
- 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
What they want
- 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