NVIDIA

NVIDIA

Posted via Workday

Datacenter GPU Power Architect

Posted Aug 5, 2026

Role at a glance

Salary
$116K – $218.5K/yr
Location
2 Locations, California, United States
Work arrangement
On-site
Employment
Full-time
Experience
2+ years of experience related to Power / Performance estimation and optimization techniques
Education
MSEE/MSCE, or equivalent experience

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Role Summary

AI-generated

The Datacenter GPU Power Architect will join NVIDIA’s Applied Power Architecture team to develop power estimation models and tools for GPUs and systems, including DGX/HGX-based datacenters. The role focuses on improving energy efficiency and total cost of ownership across GPU, system, and datacenter architectures for AI, HPC, Automotive, GeForce, and Mobile products.

What You'll Do

  • Contribute to power estimation models and tools for GPU products and systems
  • Explore early GPU and system architectures with a focus on energy efficiency and TCO improvements
  • Perform performance-versus-power analysis and track ASIC milestones
  • Deploy machine learning techniques to develop power and performance models for GPUs, CPUs, switches, and platforms
  • Analyze GenAI/HPC workload characteristics at datacenter scale to drive hardware and software features for performance-per-watt improvements
  • Model and analyze high-speed, high-density interconnect technologies

Generated from the employer's posting. Verify important details before applying.

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Qualifications

Knowledge of energy efficient chip design fundamentals and related tradeoffs; familiarity with multi-VT, clock gating, power gating, and DVFS; understanding of processors, system-SW architectures, and performance/power modeling techniques; proficiency with Python, Pandas, NumPy, and PyTorch; familiarity with performance monitors/simulators used in modern processor architectures.

Required

  • Knowledge of energy efficient chip design fundamentals and related tradeoffs
  • Familiarity with multi-VT, Clock gating, Power gating, and Dynamic Voltage-Frequency Scaling (DVFS)
  • Understanding of processors, system-SW architectures, and 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

Original job description

Content provided by the employer

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.

NVIDIA

About the company

NVIDIA

Large Enterprise

NVIDIA is a leading technology company renowned for its graphics processing units (GPUs) and innovative computing solutions that enhance visual experiences across multiple platforms, including gaming, scientific research, and artificial intelligence. Founded in 1993, the company has expanded its offerings to include powerful AI frameworks and deep learning platforms, making significant contributions to industries such as gaming, data centers, automotive, and healthcare. NVIDIA's commitment to pushing the boundaries of visual computing continues to drive advancements in both hardware and software, positioning the company at the forefront of emerging technologies and digital transformation.