Senior Applied Power Architect - GPU

Posted 3 Days Ago
Be an Early Applicant
2 Locations
Senior level
Artificial Intelligence • Computer Vision • Hardware • Robotics • Metaverse
The Role
The Senior Applied Power Architect - GPU will invent methodologies for power estimation models/tools for GPU products, analyze power vs performance to assist in product decisions, and collaborate with system architects and product engineers on energy efficiency improvements. A strong background in energy-efficient systems and industry experience is required.
Summary Generated by Built In

We are looking for a Senior Applied Power Architect – GPU.

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, Automotive, GeForce, and Mobile products.

What you'll be doing:

  • You will be responsible for inventing flows/methodologies and building the power estimation models/tools for GPU products and AI systems such as Nvidia DGX/HGX as well as Graphics cards and MaxQ notebooks.
  • Investigate multi-die technologies and come up with innovative solutions to address packaging, interconnect, physical design, electrical and thermal challenges.
  • Drive performance vs power analysis to enable management/marketing with meaningful product decisions and customer interaction.
  • As a senior team member, you will collaborate closely with other System/SW Architects, Signal Integrity /Packaging experts and Product engineers to understand product challenges and energy efficiency improvements.

What we need to see:

  • MSEE/MSCE, preferably PhD, or equivalent experience with a specialization in low-power-processor architectures.
  • Strong knowledge of energy efficient system design fundamentals and related tradeoffs from your 3+ years of relevant industry experience.
  • Deep understanding of processors (GPU is a plus), servers, and system-SW architectures, and their performance/power modeling techniques.
  • Proficiency with Python and data analysis packages like: Pandas, NumPy, PyTorch.
  • Exposure to industry standard Power Analysis EDA tools such as PrimePower etc a plus.
  • Experience with performance monitors/simulators used in modern processor architectures.
  • Exposure to lab setup including power measurement equipment such as scope/DAQ. Your ability to analyze board-level power issues like supply voltage, over-current etc. is helpful.
  • Strong interpersonal and organizational skills and the ability & desire to work as a great teammate.

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!

The base salary range is 136,000 USD - 368,000 USD. Your base salary will be determined based on your location, experience, and the pay of employees in similar positions.

You will also be eligible for equity and benefits. NVIDIA accepts applications on an ongoing basis.

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

Python
The Company
HQ: Santa Clara, CA
21,960 Employees
On-site Workplace
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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