Senior Staff/Principal Software Engineer - GPU System Software, Onboard Execution
Zoox · Foster City, CA; Seattle, WA; Boston, MA
Extracted from the posting
Senior Staff/Principal engineer leading GPU system software for Zoox's onboard robotaxi compute, covering scheduling, multi-tenancy, and isolation of perception, prediction, and planning workloads on GPUs. Owns the multi-year roadmap to reduce onboard compute per vehicle and inference stack direction (TensorRT, CUDA, quantization).
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:
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.
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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.
Compensation: USD 339,000 – 455,000 per year salary
