Architecture Energy Modeling Engineer

Nvidia

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Quick summary

Work type: On-site
Location: Santa Clara, CA
Salary: $116,000–$189,750 / yr
Employment: Full-time
Posted: 67 days ago
Freshness: Confirmed live today
Nearby: 99+ roles within 25 mi

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Salary context

Competitive pay

How this pay compares to similar roles

Similar $181k

This role $153k

$103k $238k

below market most similar roles pay here above market

This role pays less than 62% of similar roles. Most pay $140,507–$221,062 — the blue band above. At the midpoint, this role pays about $153k versus about $181k for comparable roles.

Based on 240 similar postings.

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About Nvidia

Nvidia is a leading designer of graphics processing units (GPUs) and system-on-chip units, powering gaming, professional visualization, data centers, and artificial intelligence workloads. Industry: Semiconductors & AI Computing

Nvidia currently has 1623 open roles on FindRole.

Listed pay typically runs $184,000–$287,500 across 1110 roles with salary data.

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At a glance

TL;DR · Architecture Energy Modeling Engineer

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The Architecture Energy Modeling Engineer - New College Grad 2026 joins the Power Modeling, Methodology and Analysis Team to research, develop, and deploy methodologies for energy-efficient products. This role involves building energy models that integrate into architectural simulators, RTL simulation, emulation, and silicon platforms. You will develop Machine Learning based power models to analyze and reduce power consumption for GPUs, CPUs, and Tegra SOCs. Key responsibilities include developing workflows to train models using ML and statistical techniques, estimating data movement power, and correlating predicted energy across design cycles. You will use Python, C++, and Verilog to collaborate with various engineering teams. The work focuses on gaining early insights into energy consumption for graphics and artificial intelligence workloads to influence architectural, design, and power management improvements.

Skills

Python C++ Machine Learning AI Statistical Modeling Verilog ASIC Design Computer Architecture RTL Simulation Energy Modeling Algorithms Low Power Design GPU Design Tegra SOCs

What you'll do

Develop Machine Learning based power models to analyze and reduce power consumption of NVIDIA GPUs.
Create methodologies and workflows to train models using ML and statistical techniques.
Improve model accuracy using different representations, objective functions, and learning algorithms.
Develop methodologies to estimate data movement power and energy accurately.
Correlate predicted energy from various design stages to bridge early estimates to silicon.
Integrate power-energy models into performance infrastructure platforms for combined reporting.
Develop tools to debug and suggest solutions for energy inefficiencies observed on silicon, RTL, and simulators.
Prototype new architectural features and analyze their system impact on energy efficiency.

What we're looking for

Pursuing or recently completed a MS or PhD in Electrical Engineering, Computer Engineering, Computer Science, or equivalent experience.
Strong coding skills, preferably in Python or C++ (preferred).
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 (preferred).
Ability to formulate and analyze algorithms, including their runtime and memory complexities.
Basic understanding of fundamental concepts of energy consumption, estimation, and low power design.
Good verbal/written communication and interpersonal skills.

5+ yrs exp

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