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About the role

Wafer AI: maximize intelligence per watt; autonomous AI performance engineers optimizing inference on heterogeneous hardware. 7 people, $4M raised, SF.Comp: $200K-$300K + 0.5%-1% equity.
Location: on-site 5 days FiDi SF.
Visa: Visa transfers (H-1B transfer, OPT); must already be in US; no new H1B.
Responsibilities: Ship day-zero support for new open-source models tuned for latency/throughputOptimize serving stack: batching, KV cache, speculative decoding, quantizationWrite/tune kernels in CUDA, HIP, Triton for NVIDIA, AMD, TPU, Trainium, D-MatrixDesign, deploy, operate heterogeneous multi-vendor clustersRun production inference: reliability, observability, cost per tokenTech stack: CUDA, HIP, Triton, Python, TPU, AWS TrainiumSource: https://www.paraform.com/share/wafer-ai/cmrtyva4m000j0cl7i7j9wbue1-6 yrs SWE focused on systems close to hardwareGPU kernels (CUDA/HIP/Triton), inference serving optimizationFirst-principles, resourceful, high EQ; customer-facing comfortOn-site 5 days SF; must be in US

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