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
Study, devise and implement power management strategy for NVIDIA's GPU roadmap
Research and develop solutions to address complex energy efficiency problems
Deploy machine learning techniques to develop highly accurate power and performance models of our GPUs and platforms

Requirements

Pursuing or recently completed a BS, MS, or PhD in Electrical or Computer Engineering (or equivalent experience)
Knowledge of performance simulators/monitors and Low Power architectures/techniques a 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.

Benefits

equity
benefits 📊 Check your resume score for this job Improve your chances of getting an interview by checking your resume score before you apply. Check Resume Score

Applicant Tracking System Keywords

Tip: use these terms in your resume and cover letter to boost ATS matches.

Hard Skills & Tools

GPU power managementenergy efficiencymachine learningperformance modelingPythonTensorFlowPandasNumPyPyTorchlow power architectures

Soft Skills

collaborationproblem-solvingresearchimplementation

Certifications

BS in Electrical EngineeringMS in Electrical EngineeringPhD in Electrical Engineeringequivalent experience