Nvidia Deep Learning Performance Architect 

United States, Texas 

152265330

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