Inference Optimization Engineer (local / edge runtime)

What You'll Do Profile and optimize local inference (llama.cpp-vulkan and vLLM) for latency, throughput, and memory on edge hardware Tune KV cache, continuous batching, and scheduling for interactive agent workloads Drive quantization strategy (GGUF / AWQ / GPTQ) and validate quality impact with the Post-Training team Cut CPU overhead and improve engine startup, model load, and lifecycle (start / stop / health) Benchmark across hardware tiers and publish honest performance comparisons Upstream fixes and patches to open‑source engines where it helps us What You'll Learn / Grow Into The internals of modern inference engines and where the milliseconds actually go Hardware‑aware optimization across iGPU / CPU paths (Vulkan, SYCL, oneAPI, CUDA where relevant) The quality‑vs‑speed‑vs‑memory trade space for small models Interest in local / edge AI and squeezing hardware Required Qualifications BS/MS in CS, EE, Math or related STEM field 5+ years software development background Strong in C++ and/or Python; comfortable reading systems‑level code Understands how LLM inference works (attention, KV cache, decoding) Has profiled and optimized real performance problems (CPU or GPU) and can prove the speedup Linux, build systems, and low‑level debugging expertise Preferred Qualifications Hands‑on with llama.cpp, vLLM, ggml, or similar engines Experience with GPU / accelerator programming (Vulkan, CUDA, SYCL, Metal) or SIMD / CPU kernels Familiarity with quantization formats and their quality trade‑offs Open‑source contributions to inference engines Annual Salary Range US: $170,500.00 - 315,490.00 USD Work Model This role will be eligible for a hybrid work model allowing employees to split their time between working on‑site at their assigned Intel site and off‑site. EEO Statement All qualified applicants will receive consideration for employment without regard to race, color, religion, religious creed, sex, national origin, ancestry, age, physical or mental disability, medical condition, genetic information, military and veteran status, marital status, pregnancy, gender, gender expression, gender identity, sexual orientation, or any other characteristic protected by local law, regulation, or ordinance. #J-18808-Ljbffr