Senior Inference Engineer, GPU Kernel Optimization
NVIDIA· Engineer, Sys SW
Santa Clara, CA, Austin, TX, New York, NY, Seattle, WA$184k - $287.5kfull-timePosted 2mo ago
About the role
Senior role focused on GPU kernel optimization for LLM inference, driving benchmarking, model-level performance analysis, and agentic optimization across NVIDIA's inference stack.
Responsibilities
- Drive GPU kernel microbenchmarking across full configuration space for production LLM deployments.
- Perform end-to-end model performance analysis linking performance to model-level serving economics.
- Apply AI-driven analysis to diagnose performance gaps, explore kernel optimization opportunities, and validate findings with silicon measurements.
- Collaborate with compiler, hardware, kernel, and framework teams to deliver upstream improvements and production-grade performance gains.
Qualifications
- Master’s or PhD in Computer Science, Computer Engineering, or related field, or equivalent experience.
- 6+ years of relevant industry experience.
- Experience building or directing agentic AI systems — code generation, automated optimization, or multi-step reasoning workflows.
- Strong Python and C++ skills with proven software engineering fundamentals.
- Hands-on GPU profiling with CUPTI, NSYS, and NCU; ability to attribute bottlenecks across kernel execution, compiler decisions, and runtime scheduling.
- Direct experience with LLM inference frameworks such as TRT-LLM, SGLang, or vLLM; understanding of how kernel selection drives model-level throughput and latency.
- Working knowledge of GPU kernel optimization — CUDA, CUTLASS, Triton, or equivalent; ability to read PTX or SASS output.
Skills
Required:Agentic AI systemsPythonC++GPU profilingLLM inference frameworksGPU kernel optimization
Benefits
- > Equity and comprehensive benefits package as part of compensation
- Link to NVIDIA benefits: www.nvidiabenefits.com/
Last updated Jul 31, 2026. Interested? Apply on the company site.
About NVIDIA
World Leader in AI Computing
NVIDIA invents the GPU and drives advances in AI, HPC, gaming, creative design, autonomous vehicles, and robotics.
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