Senior Software Engineer, CUTLASS Performance

• Benchmark the performance of state-of-the-art deep learning models’ inference and training passes to identify key GPU kernel and fusion opportunities.
• Identify gaps between theoretical and realized performance, and suggest software improvements or model adjustments to resolve them.
• Develop tooling to automate the benchmarking, analysis, and performance optimization loop to push the limit of CUTLASS kernel performance within DL networks.
• Be the authoritative resource on kernel performance in the team and engage with teams across NVIDIA including GPU architecture, DL frameworks, and QA as the performance representative for the CUTLASS team.

Do you have experience in System performance optimization?, Do you have a Master’s degree?, * Masters or PhD degree in Computer Science, Computer Engineering, or related field (or equivalent experience).

• 3+ years of relevant industry experience.
• Strong programming skills in Python and C++.
• Experience in software performance analysis and optimization.
• Deep understanding of computer architecture and familiarity with GPUs or similar parallel processing architectures.

Ways to stand out from the crowd:

• Deep understanding of state-of-the art DL model architectures.
• Hands-on experience with performance benchmarking of DL frameworks like PyTorch, JAX, SGLang, vLLM, TRT-LLM, or others.
• Experience in developing performance models and performance regression systems.

Your base salary will be determined based on your location, experience, and the pay of employees in similar positions. The base salary range is 152,000 USD - 241,500 USD for Level 3, and 184,000 USD - 287,500 USD for Level 4.

NVIDIA’s high-performance computing platforms are powering the AI revolution across many applications and industries. Within our software stack, CUTLASS stands out as a popular open-source ecosystem dedicated to high-performance linear algebra and Tensor Core primitives. Since 2017, it has provided the community with C++ and Python abstractions to implement custom matrix multiply (GEMM) and related math and deep learning computations on NVIDIA GPUs., NVIDIA is widely considered to be one of the technology world’s most desirable employers. We have some of the most forward-thinking and hard working people in the world working for us. If you’re creative, autonomous, and love a challenge, consider joining our Deep Learning Library team and help us build the real-time, cost-effective computing platform driving our success in this exciting and quickly growing field.