Senior AI Inference Systems Engineer – GPU Kernels

NVIDIA; Seattle (WA); On-site; USD 184,000 - 288,000; Full time

Job summary

NVIDIA in Seattle, WA seeks outstanding AI systems engineers to advance the inference software stack for AI workloads. You will develop libraries, code generators, and GPU kernel technologies for NVIDIA hardware, including new abstractions and runtimes for large language models.

The role emphasizes implementing high-performance kernels, JIT compilers, and collaboration across frameworks. Strong CUDA/C/C++ and Python skills are essential, with 6+ years in ML/DL systems.

Qualifications

• Master's degree in Computer Science, Electrical Engineering, or related field (or equivalent experience); PhD are preferred.
• 6+ years (academic/ industry) experience with ML/DL systems development preferable
• Strong experience in developing or using deep learning frameworks (e.g. PyTorch, JAX, TensorFlow, ONNX, etc) and ideally inference engines and runtimes such as vLLM, SGLang, and MLC.
• Strong Python and C/C++ programming skills
• Strong experience in GPU kernel development and performance optimizations (especially using CUDA C/C++, cuTile, Triton, or similar) with hands-on experience with Matrix Multiplication

Responsibilities

• Innovating and developing new AI systems technologies for efficient inference
• Designing, implementing, and optimizing kernels for high impact AI workloads
• Designing and implementing extensible abstractions for LLM serving engines
• Building efficient just-in-time domain specific compilers and runtimes
• Collaborating closely with other engineers at NVIDIA across deep learning frameworks, libraries, kernels, and GPU arch teams
• Contributing to open source communities like FlashInfer, vLLM, and SGLang

Skills

Python

C/C++

GPU kernel development

CUDA

Deep learning frameworks

ML/DL systems

Education

Master's degree in CS/EE (or related)

PhD preferred

Tools

vLLM

SGLang

MLC

FlashInfer

Flash Attention

Job description

NVIDIA in Seattle, WA seeks outstanding AI systems engineers to advance the inference software stack for AI workloads. You will develop libraries, code generators, and GPU kernel technologies for NVIDIA hardware, including new abstractions and runtimes for large language models.

The role emphasizes implementing high-performance kernels, JIT compilers, and collaboration across frameworks. Strong CUDA/C/C++ and Python skills are essential, with 6+ years in ML/DL systems.