Datacenter GPU Power Architect

at Nvidia

📍 Santa Clara, United States

USD 116,000-218,500 per year

MIDDLE SENIOR

✅ On-site

Tech Stack
Tag name is followed by "@" symbol and proficiency level value. About proficiency levels:

1-2 — basic awareness. Minimal hands-on experience, and a rudimentary understanding of the technology's purpose;

3-6 — daily use. Comfortable and regular usage, capable of handling common tasks and challenges related to the technology;

7-9 — you are an expert, you can teach others, you know all the pitfalls and tricks;

10 — exceptional knowledge, comprehensive understanding, and adeptness in all aspects of the technology, including advanced problem-solving. Think twice before claiming or demanding such level.

AI Data Analysis @ 5 GPU @ 3 GenAI @ 3 HPC @ 3 Machine Learning Pandas @ 5 PyTorch @ 5 Python @ 5 System Architecture

Details

NVIDIA is known as a world leader in providing energy-efficient high-performance products and we continue to invest in the research and development of hyper-efficient GPU and SOC architectures. We are continually innovating in creative and unrivaled ways to improve our ability to deliver exceptional Perf/Watt solutions in a wide range of sectors and verticals. Come join NVIDIAs Applied Power Architecture team to develop state of the art GPUs to power AI, HPC, Automotive, GeForce, and Mobile products. We are looking for a Datacenter GPU Power Architect!

Responsibilities

You will be contributing to power estimation models and tools for GPU products and systems like NVIDIA DGX/HGX based datacenters.
Early GPU & System Architecture exploration with focus on energy efficiency and TCO improvements at GPU and Datacenter level.
You will help with Performance vs Power Analysis, track ASIC milestones for impactful 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.

Requirements

MSEE/MSCE, or equivalent experience with 2+ years of 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.