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

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. 

Develop and iterate data miners locating potential RotR Violations following SSO requirements

Develop and iterate on VLM/LLM workflows and pipelines for classifying RotR events

Curate golden datasets and evaluate triager precision/recall against human triage

Extend triagers from simulation to fleet/service data

Strong Python / Pyspark / SQL skills

Coursework in machine learning, computer vision, or NLP. Understanding of supervised learning, model evaluation, and common sources of dataset bias and label noise.

Analyze error cases and translate findings into pipeline improvements

Hands-on experience building production LLM/VLM applications, including agentic workflows, RAG, tool calling, evaluation, and/or fine-tuning.

Familiarity with software-engineering practices such as Git, unit testing, debugging, and code reviews.

Strong Scala skills.

Experience with Spark optimization and distributed data-processing systems.

Experience with autonomous vehicles, robotics, mapping, or transportation-related datasets.

Experience evaluating multimodal or vision-language models.

Currently enrolled in a B.S. or M.S. program in a relevant discipline.

Experience with prompt optimization, model fine-tuning, or human-in-the-loop ML systems.

Available to commit to a minimum three-month assignment.

Able to commit a minimum of 40 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.