Student Contract Worker - Machine Learning Engineer - Data Mining & VLM (Full-time)

Zoox

  • Foster City, CA
  • 1 day ago

    Highlights

    The student will be helping create or improve the data miners that generate the candidate events, help develop and evaluate the VLM triagers — curating golden datasets, measuring precision/recall against expert triage, and extending automation to new regulations and data sources. Support Zoox's Rules of the Road (RotR) program, where a miner + LLM/VLM tooling method automatically mines and triages potential road-rule violation events from simulation and fleet data.

    Numbers & Facts

    LocationFoster City, CA

    Description

    About Zoox

    Zoox is an autonomous ridehailing company building the world's first purpose-built robotaxi — fully electric, bidirectional, with no steering wheel or driver's seat. Backed by Amazon and founded to make transportation safer, cleaner, and more accessible, Zoox designs its vehicles entirely around the rider. We're currently operating in Las Vegas and San Francisco, with Austin and Miami on the horizon, and testing underway across seven U.S. markets.

    About Our Part-Time Student Worker Program

    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.

    Role Overview

    Support Zoox's Rules of the Road (RotR) program, where a miner + LLM/VLM tooling method automatically mines and triages potential road-rule violation events from simulation and fleet data. The student will be helping create or improve the data miners that generate the candidate events, help develop and evaluate the VLM triagers — curating golden datasets, measuring precision/recall against expert triage, and extending automation to new regulations and data sources. 

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