Senior Architecture Energy Modeling Engineer

What you'll do

• Develop Machine Learning based power models to analyze and reduce power consumption of NVIDIA GPUs.
• Create methodologies and workflows to train models using ML and statistical techniques.
• Improve model accuracy using various representations, objective functions, and learning algorithms.
• Develop methodologies to accurately estimate data movement power and energy.
• Correlate predicted energy from different design stages to bridge early estimates to silicon.
• Integrate power-energy models into performance infrastructure platforms for combined reporting.
• Develop tools to debug and suggest solutions for energy inefficiencies observed on silicon, RTL, and simulators.
• Prototype new architectural features and analyze their system impact on energy efficiency.

What we're looking for

• MS or PhD in Electrical Engineering, Computer Engineering, Computer Science, or equivalent experience.
• 5+ years of experience.
• Strong coding skills, preferably in Python and C++ (preferred).
• Background in machine learning, AI, and/or statistical modeling.
• Background in computer architecture and interest in energy-efficient GPU designs.
• Familiarity with Verilog and ASIC design principles (preferred).
• Ability to formulate and analyze algorithms, including their runtime and memory complexities.
• Basic understanding of fundamental concepts of energy consumption, estimation, and low power design.