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Nvidia Deep Learning Performance Architect 
United States, Texas 
152265330

18.08.2024

What you’ll be doing:

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

  • Prototype key deep learning and data analytics algorithms and applications

  • 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

  • Actively collaborate with software, product and research teams to guide the direction of deep learning HW and SW

What we need to see:

  • MS or PhD in Computer Science, Computer Engineering, Electrical Engineering or equivalent experience

  • 3+ years of relevant work experience

  • Strong background in computer architecture and deep learning

  • Expert programming skills in Python, C, C++

  • Experience with performance and power modeling, architecture simulation, profiling, and analysis

Ways to stand out from the crowd:

  • Background in large scale distributed systems architectures and / or a background with GPU Computing and parallel programming models such as CUDA

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

  • Experience with the architecture of or workload analysis on other DL accelerators

You will also be eligible for equity and .