Senior Architecture Energy Modeling Engineer

Nvidia

Confirmed live 2 days ago High trust

Quick summary

Work type: On-site
Location: Santa Clara, CA
Salary: $136,000–$218,500 / yr
Posted: 21 days ago
Freshness: Confirmed live 2 days ago
Nearby: 99+ roles within 25 mi

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Salary context

Competitive pay

How this pay compares to similar roles

Similar $201k

This role $177k

$124k most similar roles pay here $247k

This role pays less than 55% of similar roles. Most pay $165,937–$235,100 — the shaded band above. At the midpoint, this role pays about $177k versus about $201k 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 896 open roles on FindRole.

Listed pay typically runs $184,000–$287,500 across 876 roles with salary data.

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At a glance

TL;DR · Senior Architecture Energy Modeling Engineer

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As a Senior Architecture Energy Modeling Engineer on the Power Modeling, Methodology and Analysis Team, you will research, develop, and deploy methodologies to improve energy efficiency for GPUs, CPUs, and Tegra SOCs. You will build Machine Learning based power models to analyze and reduce consumption across various workloads while collaborating with architects, ASIC design engineers, and performance teams. Your daily work involves developing workflows using ML or statistical techniques, improving model accuracy through different learning algorithms, and estimating data movement energy. You will integrate these models into architectural simulators, RTL simulation, and silicon platforms to provide early insights into graphics and artificial intelligence workloads. Required skills include Python, C++, machine learning, and computer architecture knowledge. You must be able to analyze algorithm complexity and utilize your expertise in electrical or computer engineering to influence power management improvements.

Skills

Machine Learning Python C++ Computer Architecture ASIC Design Verilog Statistical Modeling RTL Simulation Power Modeling Energy Modeling Silicon Platforms GPU Design Low Power Design

What you'll do

Develop Machine Learning based power models to analyze and reduce energy consumption of GPUs.
Create methodologies and workflows to train power models using ML and statistical techniques.
Improve model accuracy by experimenting with different representations, objective functions, and learning algorithms.
Develop methodologies to accurately estimate the power and energy costs of data movement.
Correlate predicted energy from early design stages through to final silicon production.
Integrate power and energy models into performance infrastructure platforms for combined reporting.
Build tools to debug and resolve energy inefficiencies observed in silicon, RTL, and architectural simulators.
Prototype new architectural features and analyze their impact on system energy efficiency.

What we're looking for

MS or PhD in Electrical Engineering, Computer Engineering, Computer Science, or equivalent experience.
5+ years of relevant experience.
Strong coding skills, preferably in Python and C++.
Background in machine learning, AI, and/or statistical modeling.
Background in computer architecture and interest in energy-efficient GPU designs.
Ability to formulate and analyze algorithms while commenting on runtime and memory complexities.
Basic understanding of fundamental concepts of energy consumption, estimation, and low power design.
Familiarity with Verilog and ASIC design principles (preferred).

Power Methodology and Modeling Engineer

Nvidia

Austin, TX 129 days ago $116,000–$189,750

Python C++ Machine Learning VLSI Digital Design Computer Architecture PowerBI OpenSearch Statistical Modeling Post-silicon Emulation RTL Design

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