NVIDIA is developing processor and system architectures that accelerate machine learning, automotive and high performance computing (HPC) applications. We are seeking a strong candidate to do performance analysis and kernels development for NVIDIA's new architectures. Your work will play a critical role in shaping the future of deep learning hardware and software, ensuring optimal performance for next-generation AI applications. This position offers the opportunity to make a meaningful impact in a fast-moving, technology focused company. What you'll be doing: + Design, develop, and optimize major layers in LLM (e.g attention, GEMM, inter-GPU communication) for NVIDIA's new architectures. + Implement and fine-tune kernels to achieve optimal performance on NVIDIA GPUs. + Conduct in-depth performance analysis of GPU kernels, including Attention and other critical operations. + Identify bottlenecks, optimize resource utilization, and improve throughput, and power efficiency + Create and maintain workloads and micro-benchmark suites to evaluate kernel performance across various hardware and software configurations. + Generate performance projections, comparisons, and detailed analysis reports for internal and external stakeholders. + Collaborate with architecture, software, and product teams to guide the development of next-generation deep learning hardware and software. What we need to see: + MS or PhD in relevant discipline (CS, EE, Math) + 3+ years of industry experience in GPU programming or performance optimization for DL applications. + Demonstrated experience in analyzing and improving the performance of GPU kernels, with measurable results (e.g. performance improvements, efficiency gains). + Strong programming skills in C, C++, Perl, or Python + Strong background in computer architecture + Excellent communication skills, both written and verbal. + Strong organizational and time management abilities, with the ability to prioritize tasks effectively. Ways to stand out from the crowd: + LLM FMHA or GEMM related development or optimization experience will be a plus + Expertise in CUDA programming for GPU acceleration will be a plus. + Expertise in GPU/CPU Core or MemSys architecture modeling will be a plus. #deeplearning