Senior Staff/Principal Software Engineer - GPU System Software, Onboard Execution

Posted Yesterday
Be an Early Applicant
3 Locations
Hybrid
339K-455K Annually
Senior level
Artificial Intelligence • Machine Learning • Robotics • Software • Transportation • Design • Manufacturing
Zoox is an autonomous mobility company that’s created a purpose-built robotaxi to give the world a better way to ride.
The Role
Lead the architecture and strategy for onboard GPU execution in Zoox autonomous vehicles. Define GPU scheduling, multi-tenancy, isolation, deterministic latency, compute budgets, hardware selection, and inference performance direction. Drive end-to-end reductions in latency, utilization, power, and cost across models, runtimes, middleware, and hardware. Provide technical leadership, mentor senior engineers, align cross-functional teams, and lead platform bring-up and performance optimization.
Summary Generated by Built In

Zoox is building a purpose-built robotaxi from the ground up and running it on public roads today, with riders. Every perception, prediction, and planning decision runs on an onboard compute: a fixed-power, fixed-thermal, safety-critical, real-time system. 

That makes GPU execution one of the most consequential engineering problems in the company. Each new model generation wants more compute. Each new vehicle generation needs to cost less, use less power, and stay safe. Closing that gap is not a kernel-tuning exercise. It takes an end-to-end technical vision for how the whole onboard AI workload is scheduled, shared, isolated, and sized across GPUs, and the authority to drive that vision across ML, autonomy, middleware, and hardware organizations.

You will join Zoox's Software Performance organization, which owns end-to-end performance of the onboard software stack: profiling and observability, GPU compute, and compute platform. You will work closely with Perception, Prediction, Planning, ML Infrastructure, and Hardware teams, and you will be a senior technical voice for onboard compute across the company.

We are looking for the technical leader who sets that vision. You will define how Zoox runs AI on the vehicle, and you will own the strategy for doing more with less compute on every vehicle we build next.

In this role, you will:

    • Architect onboard GPU execution. Define how perception, prediction, and planning workloads share onboard GPUs, including scheduling, multi-tenancy, isolation, and deterministic latency under contention.
    • Drive compute reduction. Own the multi-year roadmap to cut onboard compute per vehicle by setting latency and utilization budgets and landing the biggest levers across models, runtimes, middleware, and hardware in real releases.
    • Shape hardware and platform direction. Guide next-generation compute decisions (GPU and SoC selection, topology, memory budgets) with workload models and performance projections that justify them, then lead performance bring-up of each new platform.
    • Lead inference performance at scale. Set direction for the inference stack (TensorRT, CUDA, custom kernels, quantization) and partner with ML teams so models are designed for the hardware they ship on.
    • Provide technical leadership. Lead and mentor senior engineers, align directors and VPs through design docs, and make the hard calls when performance, safety, and schedule conflict.

Qualifications

  • BS in computer science, computer engineering, or related field and 10+ years in systems or performance engineering, including leading GPU or accelerator architecture across teams, or building and leading a performance engineering team.
  • Deep CUDA platform (programming model, runtime, and driver) and NVIDIA GPU microarchitecture expertise (Ampere through Blackwell, Orin, Thor).
  • Proven record setting technical direction and delivering large, measurable end-to-end gains in latency, utilization, or cost.
  • Working knowledge of ML inference optimization (TensorRT, XLA, Triton, quantization, fusion) and expert C++ on Linux.
  • Ability to align ML, systems, hardware, and leadership on a shared technical plan.

Bonus Qualifications

  • Real-time or embedded GPU experience: autonomy, robotics, AR/VR, games, or HPC.
    Production GPU multi-tenancy (MPS, MIG, priority streams).
    New GPU architecture or platform bring-up, benchmarking methodology, or workload modeling and projections.

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.

Follow us on LinkedIn

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.

Skills Required

  • Bachelor’s degree in computer science, computer engineering, or a related field
  • 10+ years of experience in systems or performance engineering
  • Experience leading GPU or accelerator architecture across teams, or building and leading a performance engineering team
  • Deep CUDA platform expertise, including the programming model, runtime, and driver
  • Expertise in NVIDIA GPU microarchitecture, including Ampere through Blackwell, Orin, and Thor
  • Proven record of setting technical direction and delivering measurable end-to-end gains in latency, utilization, or cost
  • Working knowledge of ML inference optimization, including TensorRT, XLA, Triton, quantization, and fusion
  • Expert C++ experience on Linux
  • Ability to align ML, systems, hardware, and leadership on a shared technical plan
  • Real-time or embedded GPU experience in autonomy, robotics, AR/VR, games, or HPC
  • Production GPU multi-tenancy experience with MPS, MIG, or priority streams
  • Experience with new GPU architecture or platform bring-up, benchmarking methodology, or workload modeling and projections

Zoox Compensation & Benefits Highlights

The following summarizes recurring compensation and benefits themes identified from responses generated by popular LLMs to common candidate questions about Zoox and has not been reviewed or approved by Zoox.

  • Healthcare Strength — Healthcare is extensive, with broad medical and vision options, company‑paid disability coverage, and multiple mental‑health resources. Feedback suggests coverage breadth and auxiliary programs support a wide range of needs.
  • Parental & Family Support — Family supports include paid parental leave, additional pregnancy disability time, fertility coverage, and adoption/surrogacy assistance. Backup care and family‑oriented programs further reinforce support across life stages.
  • Wellbeing & Lifestyle Benefits — Day‑to‑day perks are robust, including free daily meals, fitness subsidies, commuter support, and on‑site amenities. Feedback suggests these lifestyle benefits enhance convenience and workplace experience, especially for office‑based roles.

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The Company
HQ: Foster City, CA
2,900 Employees
Year Founded: 2014

What We Do

Zoox is an autonomous mobility company that was founded to provide a safer, cleaner, and more enjoyable future on the road. To achieve that goal, the company has spent the past 10 years creating a purpose-built robotaxi that gives the world a better way to ride.

Why Work With Us

At Zoox, we are working to solve one of the greatest technological challenges of our generation. From the beginning, we have been focused on our goal of reimagining transportation from the ground up. We are a mission-driven community of innovators working together to create a safer, cleaner, and more enjoyable future on the road.

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