Nvidia Senior Deep Learning Performance Architect 

United States, Texas 

287583568

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 workload analysis with emphasis on LLM decode architectures and performance tradeoffs

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

• Strong programming skills in Python, C++

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)