Nvidia AI Computing Architect 

China, Shanghai 

690993442

Develop innovative architectures to extend the state of the art in deep learning performance and efficiency.

Analyze performance, cost and power trade-offs by developing analytical models, simulators and test suites.

Understand and analyze the interplay of hardware and software architectures on future algorithms, programming models and applications.

Prototype key deep learning and data analytics algorithms and applications.

Actively collaborate with software, product and research teams to guide the direction of deep-learning.

BS or higher degree in a relevant technical field (CS, EE, CE, Math, etc.) with 3+ years work experience.

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

Strong background in computer architecture.

Experience with performance modeling, architecture simulation, profiling, and analysis.

Strong foundation in machine learning and deep learning.

Experience with GPU Computing and parallel programming models such as CUDA and OpenCL.

Experience with the architecture of or workload analysis on other deep learning accelerators.

Experience with deep neural network training, inference and optimization in leading frameworks (e.g. Pytorch, Tensorflow, TensorRT).

Experience with open-source AI compilers (OpenAI Triton, MLIR, TVM, XLA, etc.).