Six Figure Work

Senior Applied Power Architect - GPU

NVIDIA

Company websitenvidia.com (NVIDIA, opens in new tab)

Base salary $168,000  to $310,500

Employer-published annual base salary, USD. Advertised base range in Santa Clara, CA +1 more

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  • LocationSanta Clara, CA +1 more
  • WorkplaceWorkplace not stated
  • Status at last checkSource accepting applications when checked
  • Last checked (54 min ago) · observed since
All places named
  • Santa Clara, CA
  • Austin, TX

About this job

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.

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

What you'll be doing:

  • You will be responsible for inventing methodologies, features and techniques to address electrical/speed/power challenges for NVIDIA's next generation AI architectures such as Rubin and Feynman.

  • Drive power management initiatives to optimize power efficiency and performance, while addressing electrical/thermal and power constraints.

  • Understand process characteristics and its impact of V-F and drive analysis of various V-F tradeoffs considering Vt choices on power/other metrics and overall performance.

  • Investigate multi-die technologies and come up with innovative solutions to address packaging, interconnect, physical design, electrical and thermal challenges.

  • Analyze peak current, Di/Dt, IR and EM requirements, and collaborate closely with ASIC designers, Power Integrity, Packaging experts and Product engineers to understand challenges and formulate solutions.

What we need to see:

  • MSEE/MSCE, preferably PhD, or equivalent experience with a specialization in low-power-processor architectures.

  • Solid understanding of energy efficient system design fundamentals, performance/power modeling and related tradeoffs from your 6+ years of relevant industry experience.

  • A background in PDN design and good understanding of electrical issues such as Di/Dt, undershoot/overshoot, IR, EM, peak current, analysis/mitigation techniques are helpful.

  • Exposure and working knowledge of Python and data analysis packages like: Pandas, NumPy, PyTorch is a plus.

  • 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!

Your base salary will be determined based on your location, experience, and other objective job-related factors. The expected base salary ranges for this position are:
168,000 USD – 264,500 USD for Level 4; and 196,000 USD – 310,500 USD for Level 5.

You will also be eligible for equity and benefits.

Applications for this job will be accepted at least until November 3, 2026.

This posting is for an existing vacancy. 

NVIDIA uses AI tools in its recruiting processes.

NVIDIA is committed to fostering an inclusive 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.

Source: NVIDIA on Workday · View original posting (opens in new tab)

This range next to 6 other live NVIDIA roles with the nearest advertised base floor
Chart as a table
This range next to 6 other live NVIDIA roles with the nearest advertised base floor
RolePublished base
Senior Applied Power Architect - GPU (this listing)$168,000 - $310,500
L11 System Product Development Engineer$168,000 - $258,750
Senior Software Engineer, Network Visibility Platform - DGX Cloud$168K - $322K
Hardware Validation Procedures and Documentation Lead$168,000 - $258,750
Senior Software Engineer, Platform Engineering$168K - $322K
PhD Research Scientist, Fundamental Generative AI - New College Grad 2026$168,000 - $264,500
AI Engineering Manager - Finance$168K - $322K

Same $100K to $400K scale as every card. All NVIDIA roles · How to read the bar

Observed changes

  1. First observed on the employer's board
  2. Began meeting the published-salary criteria
Observed since
Employer-stated posting date
2026-10-30
Where this pay comes from

Location as the employer wrote it: US, CA, Santa Clara • US, TX, Austin (Levels 4-5 combined)

168,000 USD – 264,500 USD for Level 4; and 196,000 USD – 310,500 USD for Level 5.

Method
Employer text, read with fixed rules and re-verified
Checked
Rule set
us-base-v2

The pay passage appears in the employer's own job text. Fixed, deterministic rules located it, and the passage below was checked against the stored copy of the posting.

What we verified

  • The pay figures come from the employer's own listing, quoted exactly above.
  • The pay is an annual base salary in US dollars with a minimum of at least $100,000.
  • The role was publicly listed on the employer's job board when last checked.

We do not verify what the employer will actually offer, whether the employer is still recruiting for the role, or anything beyond what the employer published. Full methodology.