Student Worker - Machine Learning Engineer - Data Mining & VLM (AI)

Location: Foster City, California, United States; hybrid workplace with on-site work required at an office location

Company

Zoox develops fully electric autonomous robotaxis and the software and systems needed for autonomous ridehailing.

What you will do

• Develop and iterate data miners that identify potential Rules of the Road violations while following SSO requirements.
• Build and improve LLM/VLM workflows and pipelines for classifying road-rule events.
• Extend triagers from simulation data to fleet and service data.
• Curate golden datasets and measure triager precision and recall against expert human triage.
• Analyze error cases and convert findings into pipeline improvements.
• Expand automation to new regulations and data sources.

Requirements

• Currently enrolled in a relevant B.S. or M.S. program.
• Strong Python, PySpark, and SQL skills.
• Coursework in machine learning, computer vision, or NLP, including supervised learning, model evaluation, dataset bias, and label noise.
• Hands-on experience building production LLM/VLM applications with agentic workflows, RAG, tool calling, evaluation, or fine-tuning.
• Experience evaluating multimodal or vision-language models and familiarity with Git, unit testing, debugging, and code reviews.
• Available for at least three months, able to commit to at least 40 hours per week, and able to work on-site at an office location.

Nice to have

• Strong Scala skills.
• Experience optimizing Spark and working with distributed data-processing systems.
• Experience with autonomous vehicles, robotics, mapping, or transportation datasets.
• Experience with prompt optimization, model fine-tuning, or human-in-the-loop ML systems.

Culture & Benefits

• Part-time student worker program focused on real autonomous-technology projects.
• Collaboration with engineers and researchers working on autonomous transportation.
• Opportunity to gain practical experience beyond academic coursework.
• Confidentiality requirements apply to proprietary company information, including academic research, theses, publications, and presentations.