Senior Deep Learning Software Engineer, LLM Performance

Position Overview

NVIDIA is seeking an experienced Deep Learning Engineer passionate about analyzing and improving the performance of LLM inference. The company is rapidly growing its research and development for Deep Learning Inference and is seeking excellent Software Engineers to join the team that builds software to enable performance optimization, deployment and serving of deep learning solutions.

Responsibilities

• 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

Requirements & Skills

• 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 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)