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What you'll be doing:
You will be working on architecting GPU power features and system level power management solutions for NVIDIA products.
Collaborate closely with other Architects, Software Engineers, ASIC Design Engineers, and Product teams to study, devise and implement the power management strategy for NVIDIA's GPU roadmap.
Research and develop solutions to address complex energy efficiency problems for various GPU use-cases such as: Deep Learning training, ADAS, Gaming, Video Playback, and Idle.
Deploy machine learning techniques to develop highly accurate power and performance models of our GPUs and platforms.
What we need to see:
Pursuing or recently completed a BS, MS, or PhD in Electrical or Computer Engineering (or equivalent experience)
Knowledge of performance simulators/monitors and Low Powerarchitectures/techniquesa plus.
Working knowledge of Python, and frameworks/packages like: TensorFlow, Pandas, NumPy, PyTorch a plus.
Exposure to tools/flows such as Design Compiler, PTPX, and Power Artist etc a huge plus.
Experience with lab setup and measurement using equipment such as scope/DAQ is helpful.
Ways to stand out from the crowd:
A master’s degree/internship with a focus/projects in Low Power Architecture, power modeling, and deep learning is a plus!
You will also be eligible for equity and .
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