Staff Software Engineer - GPU System Software, Onboard Execution
Zoox · Foster City, CA
Posted November 4, 2026
AI Summary
Zoox is seeking a Staff Software Engineer to define and drive the end-to-end strategy for running AI workloads on GPUs in its purpose-built robotaxi, under fixed power, thermal, and safety-critical real-time constraints. The role involves setting the technical vision for how onboard models are scheduled, shared, isolated, and sized, and influencing ML, autonomy, middleware, and hardware teams to get more performance from less compute on each future vehicle.
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.
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