Zoox1mo ago

Part-Time Student Worker – Applied AI & LLM Workflows

Foster CityContractmid

EngineeringData SciencePart

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Overview

About the Role At Zoox, we are pushing the boundaries of autonomous mobility. Within our Autonomy Software organization,

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EngineeringData SciencePart

About the Role

At Zoox, we are pushing the boundaries of autonomous mobility. Within our Autonomy Software organization, we are pioneering a Multi-Modal Large Language Model (M-LLM) designed to fundamentally understand driving. Simultaneously, our dedicated AI productivity team is focused on leveraging advanced AI to enhance engineering and enterprise efficiency.

We are looking for a highly motivated Part-Time Student Worker to operate at the exciting intersection of these two initiatives. Working directly with the Vice President of Autonomy Software, you will explore, prototype, and strategize ways to integrate our cutting-edge M-LLM technologies into the daily workflows of our autonomy organization. If you are passionate about applied AI, productivity, and the future of autonomous driving, this is an incredible opportunity to make a tangible impact at the executive level.

Executive Collaboration: Work directly with the VP of Autonomy Software to brainstorm, define, and evaluate opportunities where M-LLMs can streamline and supercharge organizational workflows.

Cross-Functional Bridging: Act as the strategic and technical bridge between the core M-LLM Autonomy development team and the broader AI Productivity team, ensuring alignment and sharing best practices.

Prototyping & Integration: Build lightweight prototypes, scripts, or internal tools that leverage multi-modal AI to solve real-world engineering, data analysis, or administrative bottlenecks.

Exploratory Research: Stay up-to-date on the latest advancements in LLMs, M-LLMs, and agentic workflows to propose new use cases for the autonomy software division.

Education: Currently pursuing a Bachelor’s, Master’s, or Ph.D. in Computer Science, Artificial Intelligence, Software Engineering, or a closely related field.

AI/LLM Knowledge: A strong conceptual and practical understanding of Large Language Models, prompt engineering, and multi-modal AI architectures.

Technical Chops: Proficiency in Python, with experience using AI/ML frameworks, APIs, or building lightweight internal applications.

Communication Skills: Excellent verbal and written communication skills, with the ability to translate complex technical concepts into actionable workflows for executive leadership and distinct engineering teams.

Mindset: Highly proactive, scrappy, and entrepreneurial. You enjoy finding inefficiencies and building clever, AI-driven solutions to fix them.