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

Zoox; Foster City, Seattle, Boston (CA, WA, MA); Hybrid; USD 339,000 - 455,000; Full time

Benefits offered by this job

Paid time off

Zoox Stock Appreciation Rights

Amazon RSUs

Health insurance

Long-term care insurance

Long-term and short-term disability

Life insurance

Job summary

Zoox is building a purpose-built robotaxi and operates on public roads today. The role sits in Software Performance, owning end-to-end onboard software performance for GPU compute and the compute platform.

You will define how Zoox runs AI on the vehicle, aiming to do more with less compute on future platforms. You will lead senior engineers and partner with ML, hardware, and systems teams to achieve scalable, safe performance.

Qualifications

• BS in computer science, computer engineering, or related field with 10+ years in systems or performance engineering.
• Deep CUDA platform knowledge and NVIDIA GPU microarchitecture expertise (Ampere–Blackwell, Orin, Thor).
• Proven track record delivering end-to-end latency, utilization, or cost gains.
• Working knowledge of ML inference optimization (TensorRT, XLA, Triton, quantization) and expert C++ on Linux.
• Ability to align ML, systems, hardware, and leadership on a shared technical plan.

Responsibilities

• Architect onboard GPU execution: sharing workloads, scheduling, isolation, and deterministic latency.
• Drive compute reduction: multi-year roadmap to cut onboard compute per vehicle with latency/utilization budgets.
• Shape hardware and platform direction: guide next-gen compute decisions and lead performance bring-up.
• Lead inference performance at scale: direction for the inference stack and models designed for hardware.
• Provide technical leadership: mentor engineers and align leadership on performance, safety, and schedule.

Skills

CUDA platform

NVIDIA GPU microarchitecture

Performance engineering

C++ on Linux

ML inference optimization

Education

BS in CS/CE or related field

Tools

TensorRT

XLA

Triton

Job description

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 and10+ 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.

$339,000 - $455,000 a year

Base Salary Range

There are three major components to compensation for this position: salary, Amazon Restricted Stock Units (RSUs), and Zoox Stock Appreciation Rights. A sign-on bonus may be offered as part of the compensation package. The listed range applies only to the base salary. Compensation will vary based on geographic location and level. Leveling, as well as positioning within a level, is determined by a range of factors, including, but not limited to, a candidate's relevant years of experience, domain knowledge, and interview performance. The salary range listed in this posting is representative of the range of levels Zoox is considering for this position.

• Zoox also offers a comprehensive package of benefits, including paid time off (e.g. sick leave, vacation, bereavement), unpaid time off, Zoox Stock Appreciation Rights, Amazon RSUs, health insurance, long-term care insurance, long-term and short-term disability insurance, and life insurance.

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 [e-mail] 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.