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Zoox

Staff Software Engineer - GPU System Software, Onboard Execution

Posted Yesterday
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Hybrid
Boston, MA, USA
Entry level
Hybrid
Boston, MA, USA
Entry level
Lead the technical vision and strategy for GPU execution across Zoox’s onboard AI platform. Own how perception, prediction, and planning workloads are scheduled, shared, isolated, and optimized across vehicle GPUs under fixed power, thermal, cost, safety, and real-time constraints. Partner with ML, autonomy, middleware, hardware, and infrastructure teams to improve onboard compute efficiency across future vehicle generations.
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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.

 

Zoox Boston, Massachusetts, USA Office

100 Summer Street, Boston, MA, United States, 02110

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