Nvidia Deep Learning Performance Architect 

China, Shanghai 

670845494

Design and develop the architecture, interface and features of the GPU kernel library

Keep improving the quality and performance of the library and its GPU kernels

Explore and expand the boundary of innovative technologies like GPU code generation and fusion

Contribute to NVIDIA's AI business by collaborating closely with DL product teams as well as kernel development teams

MS, PhD or equivalent in relevant fields (CS, EE, Math)

2+ years of relevant work or research experience

Strong programming skills in C, C++, and Python

Excellent problem solving skills and learning capability

Experience with designing software architecture, interfaces, and building testing infrastructures

Good communication and a great teammate

Familiar with CUDA programming and GPU architecture

Familiar withTensorRT/cuDNN/cuBLASetc.

Background with DL fundamentals, frameworks, graph compilers, LLVM, MLIR etc.

Hands-on experience in development on Linux and Windows platforms, C++ build tools like CMake and DevOps tools, including Docker, Jenkins, Kubernetes etc.

Track record of mentoring junior engineers and leading a project and a team