Senior Architecture Energy Modeling Engineer

Nvidia

Quick summary

Work type
On-site
Location
Santa Clara, CA
Salary
$168,000–$264,500 / yr
Posted
146 days ago

Market check

Salary context

Above market

How this pay compares to similar roles

Similar $179k
This role $216k
$116k most similar roles pay here $280k

This role pays more than 78% of similar roles. Most pay $142,475–$216,250 — the shaded band above. At the midpoint, this role pays about $216k versus about $179k for comparable roles.

Based on 240 similar postings.

Employer

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 855 open roles on FindRole.

Listed pay typically runs $184,000–$287,500 across 843 roles with salary data.

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View all roles at Nvidia

At a glance

TL;DR · Senior Architecture Energy Modeling Engineer

Join NVIDIA as a Senior Architecture Energy Modeling Engineer on our Power Modeling, Methodology and Analysis Team, where you will develop machine learning-based power models to analyze and reduce power consumption in NVIDIA’s GPUs. Collaborating closely with architects, ASIC designers, low-power engineers, performance experts, software developers, and physical design teams, your role involves identifying key features for energy-efficient designs, developing methodologies to train accurate power/energy models using ML techniques, and integrating these models into architectural simulators and RTL platforms. You will also work on tools to debug inefficiencies in silicon and simulate new architectural features to enhance overall GPU performance per watt. Essential skills include a strong background in machine learning, computer architecture, coding proficiency in Python or C++, and knowledge of Verilog and ASIC design principles.

What you'll do

  • Develop machine learning-based power models to analyze and reduce GPU power consumption.
  • Identify key design features for building unit power/energy models using ML techniques.
  • Improve model accuracy through various representations, objective functions, and algorithms.
  • Estimate data movement power/energy accurately across different stages of the design cycle.
  • Integrate energy models into performance platforms for combined reporting of performance and power.

What we're looking for

  • 6+ years of experience in relevant technical fields with an MS or equivalent.
  • Strong coding proficiency in Python and C++.
  • Expertise in machine learning, AI, and statistical modeling techniques.
  • Background in computer architecture, focusing on energy-efficient GPU designs.
  • Familiarity with Verilog and ASIC design principles preferred.
  • Ability to analyze algorithms for runtime and memory complexities.
  • Basic understanding of energy consumption estimation and low power design concepts.

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