Architecture Energy Modeling Engineer - New College Grad 2026
Core
Develop Machine Learning-based power/energy models to analyze and reduce power consumption of NVIDIA GPUs, CPUs, and Tegra SOCs, integrating models into architectural simulators and RTL simulation.
Role type
Junior IC machine-learning engineer (power modeling)
Builds
Energy-efficient GPU architectures and power modeling workflows
Domain
Semiconductor hardware design + Machine Learning
Deliverable
production ML models
Required skills
Machine learning, statistical modeling, Python, C++, computer architecture, algorithm analysis, energy consumption estimation
Preferred skills
Verilog, ASIC design principles, low power design
Responsibilities
Develop ML-based unit power/energy models; train models using ML/statistical techniques; improve model accuracy via different representations and algorithms; estimate data movement power/energy; correlate predicted energy across design stages; integrate power models into performance platforms; prototype new architectural features and analyze system impact; suggest solutions for energy inefficiencies.
Seniority
Junior, new graduate
