Staff Software Engineer - GPU System Software, Onboard Execution

Zoox; Boston (MA); Sur place; USD 290 000 - 322 000; Plein temps

Avantages offerts par ce poste

Amazon RSUs

Zoox Stock Appreciation Rights

Sign-on bonus

Paid time off

Health insurance

Long-term disability insurance

Life insurance

Résumé du poste

Zoox is building a purpose-built robotaxi with onboard AI workloads executed on a real-time compute system. The Software Performance organization owns end-to-end performance of the onboard stack, collaborating with Perception, Prediction, and Planning teams.

You will shape how Zoox runs AI on the vehicle and own the strategy to maximize compute efficiency across upcoming platforms. You will lead architecture decisions, drive multi-year reductions in compute per vehicle, and set the direction for

Qualifications

• BS in computer science, computer engineering, or related field with 10+ years in systems or performance engineering.
• Deep CUDA platform 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.

Responsabilités

• Architect onboard GPU execution: scheduling, multi-tenancy, isolation, and deterministic latency under contention.
• Drive compute reduction via a multi-year roadmap with latency and utilization budgets across models and hardware.
• Shape hardware and platform direction with workload models and performance projections, leading platform bring-up.
• Lead inference performance at scale: define the inference stack (TensorRT, CUDA, custom kernels, quantization) with ML teams.
• Provide technical leadership: mentor engineers and align directors/VPs on design decisions when performance and safety matter.

Connaissances

GPU architecture

Performance engineering

C++ on Linux

CUDA on NVIDIA GPUs

Multitenancy/Isolation

Formation

BS in Computer Science or related

Outils

TensorRT

CUDA

Linux

Description du poste

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.

$290,000 - $322,000 biweekly

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.

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.