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 analysisand 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.
JR2003166