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Machine Learning Engineer (Student Worker, Data Mining & VLM)

Zoox

On-siteentryPosted 6d ago

Job description

  • 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

  • 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

  • We want to be transparent: this is not an internship

  • The Part-Time Student Worker Program is designed to complement your academic experience by providing meaningful, ongoing work alongside your studies

  • Rather than participating in a cohort-based program, you’ll join a team directly and contribute to real projects with real impact

  • While the program does not include structured intern programming or a pathway to full-time employment, it offers valuable opportunities to learn, develop new skills, and gain hands-on experience in a professional environment

Benefits

  • Paid parental leave

  • Affinity groups and sports clubs

  • Work from home opportunities

  • Health insurance

  • Our crew’s health and happiness is our first priority. We offer comprehensive health and mental health support, a wellbeing program, and unlimited and flexible paid time away

  • We invest in our crew—and their families—for the long term. That includes generous family planning support, caregiver support, and strong cash compensation with great equity upside

  • We look after our crew when they’re in the office too. Our famous food program is a great example, featuring a daily changing menu of local and sustainable dishes

  • There’s a busy calendar of social events at Zoox, with more sports teams than you can count. And, of course, playing with robots is an important part of the job description- 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

  • Analyze error cases and translate findings into pipeline improvements

  • Extend triagers from simulation to fleet/service data

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

  • Strong Python / Pyspark / SQL skills

  • Strong Scala skills

  • Experience with Spark optimization and distributed data-processing systems

  • 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

  • Able to commit a minimum of 40 hours per week

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

  • 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

  • Available to commit to a minimum three-month assignment