Staff Software Engineer - GPU System Software, Onboard Execution
at Zoox
- Location
- Foster City, CA; Boston, MA; Seattle, WA — US
- Mode
- On-site
- Level
- Staff+
- Posted
- Nov 4, 2026
You’ll apply on the company’s own site.
- gpu
- cuda
- inference-serving
- real-time-systems
- performance-optimization
- c++
- system-software
- autonomy
Pay context
Staff+ Infrastructure roles on this board that post annual USD salaries: median $275k, middle half $235k–$363k, across 149 postings from 24 companies.
Hiring at Zoox
80 open AI roles listed here · 25 added in the past 30 days.
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.
You’ll apply on the company’s own site.