Senior Deep Learning Performance Architect at NVIDIA enhancing AI Inference performance through innovative GPU architectures. Engage in hardware-software co-design and collaborate across teams for AI advancements.
Responsibilities
Design novel GPU and system architectures to advance the forefront of AI Inference performance and efficiency
Construct, investigate, and test popular deep learning algorithms and applications
Understand and analyze the relationship between hardware and software architectures as it influences future algorithms and applications
Build efficient power and performance models of AI inference stack, while capturing minimal but significant information to guide next-gen HW architecture
Collaborate across the company to guide the direction of AI, working with software, research, and product teams
Requirements
A MS or PhD in a relevant field (CS, EE, Math) or equivalent experience, with 5+ years of relevant experience
Strong mathematical foundation in machine learning and deep learning
Expert programming skills in C, C++, and/or Python
Familiarity with GPU computing (CUDA or similar) and HPC (MPI, OpenMP) stack
Strong knowledge and coursework in computer architecture
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