Senior LLM Inference Performance Engineer
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Key Responsibilities
Optimize decode latency, throughput, and LLM serving costs Work with Trainium2, Trainium3, Neuron SDK, and vLLM Evaluate speculative decoding and Multi-Token Prediction for Qwen models Profile and benchmark GPU and Trainium production workloads Optimize prefill, decode, batching, KV-cache, and parallelism
Requirements:
Five-plus years in Machine Learning or Systems Engineering Two-plus years with production LLM inference or serving Strong Python and PyTorch programming experience Experience with vLLM, TensorRT-LLM, SGLang, or Triton Understanding of prefill, decode, batching, and KV-cache management Apply inference performance engineering, Python, PyTorch, and accelerator optimization across demanding production LLM workloads. #J-18808-Ljbffr
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