Analyze state of the art DL networks (LLM etc.), identify and prototype performance opportunities to influence SW and Architecture team for NVIDIA's current and next gen inference products.
Develop analytical models for the state of the art deep learning networks and algorithm to innovate processor and system architectures design for performance and efficiency.
Specify hardware/software configurations and metrics to analyze performance, power, and accuracy in existing and future uni-processor and multiprocessor configurations.
Collaborate across the company to guide the direction of next-gen deep learning HW/SW by working with architecture, software, and product teams.
Requirements
BS or higher degree in a relevant technical field (CS, EE, CE, Math, etc.)
Strong programming skills in Python, C, C++.
Strong background in computer architecture.
Experience with performance modeling, architecture simulation, profiling, and analysis.
Prior experience with LLM or generative AI algorithms.
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