Datacenter GPU Power Architect - New College Grad 2024

at Nvidia

📍 Santa Clara, United States

$108,000-201,200 per year

JUNIOR
✅ On-site

SCRAPED

Used Tools & Technologies

Not specified

Required Skills & Competences ?

Python @ 5 Machine Learning @ 3 Data Analysis @ 5 System Architecture @ 3 PyTorch @ 5 Pandas @ 5

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.

Responsibilities

  • You will be contributing 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.
  • You will 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.

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.

NVIDIA is widely considered to be one of the technology world’s most desirable employers. Our products are leading the way with groundbreaking developments in Artificial Intelligence, High-Performance Computing and Visualization. We have some of the most forward-thinking and hardworking people in the world working for us. Do you love the challenge of crafting the fastest and most power-efficient chips in their class? If so, we want to hear from you!