Six Figure Work

Architecture Energy Modeling Engineer - New College Grad 2026

NVIDIA

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

Base salary $116,000  to $218,500

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

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  • LocationSanta Clara, CA
  • WorkplaceWorkplace not stated
  • Status at last checkSource accepting applications when checked
  • Last checked (1 h ago) · observed since

About this job

Today, NVIDIA is tapping into the unlimited potential of AI to define the next era of computing. An era in which our GPU acts as the brains of computers, robots, and self-driving cars that can understand the world. Doing what’s never been done before takes vision, innovation, and the world’s best talent. As an NVIDIAN, you’ll be immersed in a diverse, encouraging environment where everyone is inspired to do their best work. Come join the team and see how we can make a lasting impact on the world. 

We are now looking for an Architecture Energy Modeling Engineer to join our Power Modeling, Methodology and Analysis Team! Our team is responsible for researching, developing, and deploying methodologies to help NVIDIA's products become more energy efficient; and is responsible for building energy models that integrate into architectural simulators, RTL simulation, emulation and silicon platforms. Key responsibilities include developing Machine Learning based power models to analyze and reduce power consumption of NVIDIA GPUs. You will collaborate with Architects, ASIC Design Engineers, Low Power Engineers, Performance Engineers, Software Engineers, and Physical Design teams to study and implement energy modeling techniques for NVIDIA's next generation GPUs, CPUs and Tegra SOCs. Your contributions will help us gain early insight into energy consumption of graphics and artificial intelligence workloads, and will allow us to influence architectural, design, and power management improvements.

What you'll be doing:

  • Work with architects, designers, and performance engineers to develop an energy-efficient GPU.

  • Identify key design features and workloads for building Machine Learning based unit power/energy models.

  • Develop and own methodologies and workflows to train models using ML and/or statistical techniques.

  • Improve the accuracy of trained models by using different model representations, objective functions, and learning algorithms.

  • Develop methodologies to estimate data movement power/energy accurately.

  • Correlate the predicted energy from models built at different stages of the design cycle, with the goal of bridging early estimates to silicon.

  • Work with performance infrastructure teams to integrate power/energy models into their platforms to enable combined reporting of performance and power for various workloads.

  • Develop tools to debug energy inefficiencies observed in various workloads run on silicon, RTL, and architectural simulators. Identify and suggest solutions to fix the energy inefficiencies.

  • Prototype new architectural features, build an energy model for those new features, and analyze the system impact.

  • Identify, suggest, and/or participate in studies for improving GPU perf/watt.

What we need to see:

  • Pursuing or recently completed a MS or PhD in Electrical Engineering, Computer Engineering, Computer Science or equivalent experience.

  • Strong coding skills, preferably in Python, C++.

  • Background in machine learning, AI, and/or statistical modeling.

  • Background in computer architecture and interest in energy-efficient GPU designs.

  • Familiarity with Verilog and ASIC design principles is a plus.

  • Ability to formulate and analyze algorithms, and comment on their runtime and memory complexities.

  • Basic understanding of fundamental concepts of energy consumption, estimation, and low power design.

  • Desire to bring quantitative decision-making and analytics to improve the energy efficiency of our products.

  • Good verbal/written communication and interpersonal skills.

NVIDIA is widely considered to be one of the technology world’s most desirable employers. We have some of the most forward-thinking and hardworking people in the world working for us. If you're creative and autonomous, 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:
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 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)

Pay in context

This role's base floor ($116,000) is above 4% of the 1,731 Data & ML roles in California listed on this site; 6 others list the same floor. Their median floor is $184,000; the middle half runs from $154,300 to $224,000.

Only jobs on this site count, and each one publishes a base salary of $100,000 or more, so this compares six-figure jobs with each other, not with the whole market. Computed Nov 7, 2026.

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
Architecture Energy Modeling Engineer - New College Grad 2026 (this listing)$116,000 - $218,500
Global Virtual Card Payment Administrator$116,000 - $195,500
Forward Deployed Engineer - Finance$116K - $230K
Customer Solutions Architect, Applications Engineering$116,000 - $189,750
Senior Revenue Accountant – Revenue Accounting Operations$116,000 - $195,500
ASIC Design Engineer – Clocks IP$116,000 - $218,500
Deep Learning Compiler Verification Engineer$116,000 - $189,750

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 (Levels 2-3 combined)

116,000 USD – 189,750 USD for Level 2; and 136,000 USD – 218,500 USD for Level 3.

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.

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