Datacenter GPU Power Architect

Summary

Join NVIDIA's Applied Power Architecture team to develop state-of-the-art GPUs for AI, HPC, Automotive, GeForce, and Mobile products. As a Datacenter GPU Power Architect, you will contribute to power estimation models and tools, deploy machine learning techniques, and understand workload characteristics for GenAI/HPC workloads.

Requirements

• Pursuing a MSEE/MSCE, or equivalent experience related to Power / Performance estimation and optimization techniques
• Knowledge of energy efficient chip design fundamentals and related tradeoffs
• Familiarity with low power design techniques such as multi-VT, Clock gating, Power gating, and Dynamic Voltage-Frequency Scaling (DVFS)
• Understanding of processors (GPU is a plus), system-SW architectures, and their performance/power modeling techniques
• Proficiency with Python and data analysis packages like: Pandas, NumPy, PyTorch
• Familiarity with performance monitors/simulators used in modern processor architectures

Responsibilities

• Contribute to power estimation models and tools for GPU products and systems like NVIDIA DGX
• Early GPU & System Architecture exploration with focus on energy efficiency and TCO improvements at GPU and Datacenter level
• Help with Performance vs Power Analysis for NVIDIA future product lineup
• Deploy machine learning techniques to develop highly accurate power and performance models of our GPUs, CPUs, Switches, and platforms
• Understand the workload characteristics for GenAI/HPC workloads at Datacenter Scale (multi-GPU) to drive new HW/SW features for Perf@Watt improvements
• Modeling & analysis of cutting-edge technologies like high speed & high-density interconnects