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.

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.

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.

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.