Senior Deep Learning Software Engineer, LLM Performance

NVIDIA is seeking a Senior Deep Learning Software Engineer to optimize the performance of LLM inference. The role involves developing GPU-accelerated software like TensorRT and Triton, collaborating with cross-functional teams, and contributing to open-source frameworks.

• Performance optimization, analysis, and tuning of LLM, VLM and GenAI models for DL inference, serving and deployment in NVIDIA/OSS LLM frameworks. Scale performance of LLM models across different architectures and types of NVIDIA accelerators. Scale performance for max throughput, minimum latency and throughput under latency constraints. Contribute features and code to NVIDIA/OSS LLM frameworks, inference benchmarking frameworks, TensorRT, and Triton. Work with cross-collaborative teams across generative AI, automotive, image understanding, and speech understanding to develop innovative solutions.

• Bachelors, Masters, PhD, or equivalent experience in relevant fields (Computer Engineering, Computer Science, EECS, AI). At least 8 years of relevant software development experience. Excellent Python/C/C++ programming, software design and software engineering skills. Experience with a DL framework like PyTorch, JAX, TensorFlow.

• Prior experience with an LLM framework or DL compiler in inference, deployment, algorithms, or implementation. Prior experience with performance modeling, profiling, debug, and code optimization of a DL/HPC/high-performance application. Architectural knowledge of CPU and GPU. GPU programming experience (CUDA or OpenCL).