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.
$339,000 - $455,000 a year
Base Salary RangeThere 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.
