Senior Deep Learning Software Engineer, Inference
NVIDIA AI · Orange County, CA · Yesterday
EngineeringFull-time
About the role
NVIDIA seeks a Senior Software Engineer specializing in Deep Learning Inference for our growing team. The role involves designing, building, and optimizing GPU-accelerated software for AI applications. Key responsibilities include performance optimization, feature contributions, and collaboration with cross-functional teams.
Responsibilities
- Performance optimization, analysis, and tuning of DL models in various domains like LLM, Multimodal and Generative AI.
- Scale performance of DL models across different architectures and types of NVIDIA accelerators.
- Contribute features and code to NVIDIA’s inference libraries, vLLM and SGLang, FlashInfer and LLM software solutions.
- Work with cross-collaborative teams across frameworks, NVIDIA libraries, and inference optimization innovative solutions.
Requirements
- Masters or PhD or equivalent experience in relevant field (Computer Engineering, Computer Science, EECS, AI).
- 5+ years of relevant software development experience.
- Excellent C/C++ programming and software design skills.
- SW Agile skills are helpful and Python experience is a plus.
- Prior experience with training, deploying or optimizing the inference of DL models in production is a plus.
- Prior background with performance modeling, profiling, debug, and code optimization or architectural knowledge of CPU and GPU is a plus.
- GPU programming experience (CUDA, OAI TRITON or CUTLASS) is a plus.
Qualifications
- Experience with deep learning software projects, such as PyTorch, vLLM, and SGLang to drive advancements in the field.
- Experience with Multi GPU Communications (NCCL, NVSHMEM).
Skills
- Open-source tools and plugins including CUTLASS, OAI Triton, NCCL, and CUDA kernels.
Benefits
- Competitive salaries and a comprehensive benefits package.
- Opportunities for equity and benefits.
Pay
- Base salary range: $152,000 - $241,500 for Level 3, and $184,000 - $287,500 for Level 4.
Schedule
- Full-time position.