Contract Student Worker Automation & Behavioral Science Engineer

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 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

Qualifications

• 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

Bonus Qualifications

• 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

Program Requirements

• 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 20 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