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Nvidia Deep Learning Performance Architect China, Shanghai 670845494
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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
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