Student Worker - Machine Learning Engineer - Data Mining & VLM

Responsibilities

• 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

Required Qualifications

• 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.

Bonus Qualifications

• Strong Scala skills.
• Experience with Spark optimization and distributed data-processing systems.
• Experience with autonomous vehicles, robotics, mapping, or transportation-related datasets.

Program Requirements

• 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.