Part Time Student Worker - Performance Optimization & Agentic Systems

Zoox - Part Time Student Worker - Performance Optimization & Agentic Systems

Part Time Student Worker - Performance Optimization & Agentic Systems

Foster City, CA / San Diego, CA / Seattle, WA

Software - Software /

Contract /

Hybrid

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About Zoox

Zoox is transforming mobility with fully autonomous, electric vehicles designed from the ground up for a driverless future. Our mission is to make transportation safer, more sustainable, and accessible to everyone. At Zoox, innovation, collaboration, and a bold vision for the future drive everything we do.

About Our Part Time Student Worker Program

Zoox's program offers hands-on experience with cutting-edge technology, mentorship from some of the industry's brightest minds, and the opportunity to make meaningful contributions to real projects. We seek part time student workers who demonstrate strong academic performance, engagement beyond the classroom, intellectual curiosity, and a genuine interest in Zoox's mission.

Project Overview

Zoox is seeking a highly detail-oriented and methodical student contractor to join our platform architecture team. The primary focus of this role is to design and execute rigorous performance optimization experiments for software processes running on high-performance CPU/GPU platforms (NVIDIA).

In this role, you will:

• Ensure that experiments are reproducible, profiling data is meticulously captured, and edge cases are thoroughly investigated
• Thrive on precision
• You will work at the intersection of traditional hardware-aware optimization and cutting-edge agentic systems, using tools like Claude to develop LLM-based agents that can assist in the optimization lifecycle

Qualifications:

• Strong Mathematical Foundation: Demonstrated proficiency in Linear Algebra, Control Theory, or Stochastic Optimization to model autonomy and performance bottlenecks
• Hardware-Aware Optimization: A deep academic or project-based understanding of computer architecture (NVIDIA platforms) to optimize for memory bandwidth and high-throughput TFLOPS

Agentic Systems & Analysis: Experience experimenting with LLM-based agents and a disciplined approach to systems profiling and software engineering

• Operational Style: You must be exceptionally detail-oriented and careful in your execution, prioritizing accuracy and deep-dive analysis over speed

Program Requirements:

• Currently pursuing a B.S. or M.S., in a relevant engineering field
• Available for a 6 month project
• Able to commit to at least 20 hours per week
• Ability to commute on-site to one of our offices
• Student Worker may not use proprietary Zoox information in university theses, publications, or share it outside

$30 per hour.

This is a contract position and employment for this position will be through a vendor contracted with Zoox. The hourly pay range is posted and you will be eligible for a benefits package as offered by the vendor.

About Zoox

Zoox is developing the first ground-up, fully autonomous vehicle fleet and the supporting ecosystem required to bring this technology to market. Sitting at the intersection of robotics, machine learning, and design, Zoox aims to provide the next generation of mobility-as-a-service in urban environments. We're looking for top talent that shares our passion and wants to be part of a fast-moving and highly execution-oriented team.

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Accommodations

If you need an accommodation to participate in the application or interview process please reach out to [email protected] or your assigned recruiter.

A Final Note:

You do not need to match every listed expectation to apply for this position. Here at Zoox, we know that diverse perspectives foster the innovation we need to be successful, and we are committed to building a team that encompasses a variety of backgrounds, experiences, and skills.

We may use artificial intelligence (AI) tools to support parts of the hiring process, such as reviewing applications, analyzing resumes, or assessing responses. These tools assist our recruitment team but do not replace human judgment. Final hiring decisions are ultimately made by humans. If you would like more information about how your data is processed, please contact us.

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