Architect onboard GPU execution. Define how perception, prediction, and planning workloads share
Drive compute reduction. Own the multi-year roadmap to cut onboard compute per vehicle by setting
Shape hardware and platform direction. Guide next-generation compute decisions (GPU and SoC
Lead inference performance at scale. Set direction for the inference stack (TensorRT, CUDA, custom
Provide technical leadership. Lead and mentor senior engineers, align directors and VPs through

🎯 Requirements

BS in computer science, computer engineering, or related field and 10+ years in systems or
Deep CUDA platform (programming model, runtime, and driver) and NVIDIA GPU microarchitecture
Proven record setting technical direction and delivering large, measurable end-to-end gains in
Working knowledge of ML inference optimization (TensorRT, XLA, Triton, quantization, fusion) and
Ability to align ML, systems, hardware, and leadership on a shared technical plan.

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