Senior Deep Learning Software Engineer, LLM Performance

About the Role

NVIDIA is seeking an experienced Deep Learning Engineer passionate about analyzing and improving the performance of LLM inference! NVIDIA is rapidly growing our research and development for Deep Learning Inference and is seeking excellent Software Engineers at all levels of expertise to join our team. Companies around the world are using NVIDIA GPUs to power a revolution in deep learning, enabling breakthroughs in areas like LLM, Generative AI, Recommenders and Vision that have put DL into every software solution. Join the team that builds the software to enable the performance optimization, deployment and serving of these DL solutions. We specialize in developing GPU-accelerated Deep learning software like TensorRT, DL benchmarking software and performant solutions to deploy and serve these models.

You will collaborate with the deep learning community to implement the latest algorithms for public release in TensorRT LLM, VLLM, SGLang and LLM benchmarks. You will identify performance opportunities and optimize SoTA LLM models across the spectrum of NVIDIA accelerators, from datacenter GPUs to edge SoCs. You will also implement LLM inference, serving and deployment algorithms and optimizations using TensorRT LLM, VLLM, SGLang, Triton and CUDA kernels. This role involves working and collaborating with a diverse set of teams involving performance modeling, performance analysis, kernel development and inference software development.

What you'll be doing:

• 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.

What we need to see:

• 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.

Ways to stand out from the crowd:

• Prior experience with a LLM framework or a 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).