Source description
About the role
Qualifications
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CUDA + GPU inference optimization
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vLLM, SGLang, or TensorRT-LLM experience
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KV caching, paged attention, batching, token streaming, etc.
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Distributed compute (with GPUs is a super plus)
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No degree required
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Company
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Luminal (YC S25) builds an AI compiler and serving stack that makes models 10x faster and production ready with one line.
Role
Founding, on site in downtown SF. Ship low latency, high throughput model serving on Luminal Cloud.
Day to day responsibilities:
Deploy and tune models with optimizations like KV caching, paged attention, sequence packing, etc.
Conducting model performance reviews
Improve scheduler, batcher, autoscaling; profile latency, cost, utilization
Sometimes write kernels and, yes, occasional tasteful shitposting
More at Luminal