Datacenter GPU Power Architect

Reposted 3 Days Ago
Be an Early Applicant
2 Locations
In-Office
108K-213K Annually
Junior
Artificial Intelligence • Computer Vision • Hardware • Robotics • Metaverse
The Role
Develop power estimation models for GPUs, analyze performance vs power metrics, and optimize chip design for efficiency in datacenters.
Summary Generated by Built In

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!

What you'll be doing:

  • 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.

What we need to see:

  • 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.

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!

Your base salary will be determined based on your location, experience, and the pay of employees in similar positions. The base salary range is 116,000 USD - 189,750 USD for Level 2, and 136,000 USD - 218,500 USD for Level 3.

You will also be eligible for equity and benefits.

Applications for this job will be accepted at least until January 13, 2026.

This posting is for an existing vacancy. 

NVIDIA uses AI tools in its recruiting processes.

NVIDIA is committed to fostering a diverse work environment and proud to be an equal opportunity employer. As we highly value diversity in our current and future employees, we do not discriminate (including in our hiring and promotion practices) on the basis of race, religion, color, national origin, gender, gender expression, sexual orientation, age, marital status, veteran status, disability status or any other characteristic protected by law.

Top Skills

Numpy
Pandas
Python
PyTorch
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The Company
HQ: Santa Clara, CA
21,960 Employees
Year Founded: 1993

What We Do

NVIDIA’s invention of the GPU in 1999 sparked the growth of the PC gaming market, redefined modern computer graphics, and revolutionized parallel computing. More recently, GPU deep learning ignited modern AI — the next era of computing — with the GPU acting as the brain of computers, robots, and self-driving cars that can perceive and understand the world. Today, NVIDIA is increasingly known as “the AI computing company.”

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