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

Requirements

Masters 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)

Benefits

equity
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Applicant Tracking System Keywords

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Hard Skills & Tools

AI systems technologieskernels optimizationLLM serving enginesdomain specific compilersjust-in-time compilationdeep learning frameworksPythonC/C++GPU kernel developmentperformance optimization

Soft Skills

collaboration

Certifications

Masters degree in Computer ScienceMasters degree in Electrical EngineeringPhD