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Nvidia Senior Deep Learning Performance Architect 
United States, Texas 
528098966

Yesterday
US, CA, Santa Clara
US, TX, Austin
time type
Full time
posted on
Posted 26 Days Ago
job requisition id

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 algorithms and applications

  • Analyze performance, cost and energy trade-offs by developing analytical models, simulators and test suites

  • Characterize power and performance on silicon parts and translate the learnings to architecture features and simulators.

  • 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:

  • A Masters Degree (or equivalent experience) and 6+ years of meaningful relevant experience or PhD and 3+ years of experience in Computer Science, Electrical Engineering, Computer Engineering, or related field

  • Strong foundation in Deep Learning model architectures and performance tradeoffs

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

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

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

Ways to stand out from the crowd:

  • 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, JAX)

You will also be eligible for equity and .