NVIDIA Corporation

Architecture Energy Modeling Engineer - New College Grad 2026

NVIDIA Corporation • $116K — $218K *
Santa Clara, CA 95051In-Person
Energy & Utilities
Less than 5 years of experience
Today
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Job Overview by Ladders

Qualifications

  • Pursuing or recently completed MS or PhD in Electrical/Computer Engineering or equivalent.
  • Strong coding skills in Python and C++.
  • Experience in machine learning, AI, and statistical modeling.
  • Knowledge of computer architecture with an interest in energy-efficient GPUs.
  • Familiarity with Verilog and ASIC design is advantageous.
  • Ability to analyze algorithms regarding runtime and memory.
  • Basic understanding of energy consumption estimation and low power design.

Responsibilities

  • Collaborate with architects and engineers to design energy-efficient GPUs.
  • Identify design features for Machine Learning-based power models.
  • Own methodologies to train models using ML/statistical techniques.
  • Enhance model accuracy through varied representations and learning algorithms.
  • Estimate data movement energy accurately with developed methodologies.
  • Correlate energy predictions across design stages to silicon outcomes.
  • Integrate power models into platforms for performance and power reporting.
  • Debug energy inefficiencies and propose solutions for improvements.
  • Prototype architectural features and assess their energy model impacts.
  • Conduct studies aimed at enhancing GPU performance per watt.

Benefits

  • Eligible for equity and comprehensive benefits package.
Full Job Description
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.
Your base salary will be determined based on your location, experience, and the pay of employees in similar positions. The base salary range is 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 August 25, 2026. This posting is for an existing vacancy. NVIDIA uses AI tools in its recruiting processes.

About NVIDIA Corporation

Nvidia, a global leader in graphics, gaming, and AI technology, offers Nvidia careers and internship opportunities for those passionate about driving innovation in the tech industry. you'll find a company committed to growth, teamwork, and leadership in computer science and machine learning domains.

About Nvidia

A Pioneer in Technology and Innovation

Nvidia has cemented its reputation as a powerhouse in developing advanced graphics processing units (GPUs) and has significantly contributed to the gaming industry's evolution. Moreover, its foray into AI and machine learning has opened new frontiers in technology, making Nvidia a beacon of innovation and a desirable workplace for ambitious tech professionals.

Job Opportunities

Diverse Positions in a Dynamic Field

Nvidia is continuously on the lookout for talented individuals across various domains, including hardware and software engineering, product design, marketing, and sales. Employment opportunities at Nvidia are vast, catering to a wide range of expertise and career aspirations.

Employment in Hardware and Graphics

For those fascinated by the intricacies of hardware and graphics technology, Nvidia offers positions that sit at the forefront of gaming and computing advancements.

Growth in Machine Learning and AI

Nvidia's leadership in AI and machine learning has created numerous vacancies for specialists eager to contribute to groundbreaking projects.

Recruitment in Computer Science

With the constant demand for innovation, Nvidia's recruitment efforts focus on computer science experts capable of pushing the boundaries of what's possible.

Internship Program

Opening Doors to Future Innovators

Nvidia's internship program is designed to nurture the next generation of technology leaders, offering hands-on experience in a culture that celebrates creativity and teamwork.

Benefits and Culture

Interns at Nvidia enjoy a plethora of benefits, from competitive stipends to mentorship opportunities, all within an environment that values growth and learning.

Opportunities for Students

Whether you're an undergraduate, a master's student, or a Ph.D. candidate, Nvidia's internships provide a real-world glimpse into the tech industry, offering valuable experience in various technology fields.

Pathways to Full-Time Employment

Many interns have transitioned into full-time positions, marking the start of successful careers at Nvidia. The internship program is more than a stepping stone into the company; it’s an investment in the professional development of interns. The goal is to ensure that interns are well-equipped for future challenges.

Nvidia Careers: More Than Just a Job

Nvidia offers more than just a job to its employees; it provides a front-row seat on the journey into the future of technology. Nvidia stands as a pillar of innovation with its vast opportunities in hardware, graphics, gaming, machine learning, and computer science. Nvidia careers serve as a launching pad for talented workers who aim to redefine the technological landscape. Whether through full-time positions or internships, joining Nvidia means contributing to a legacy of breakthroughs and becoming part of a global community dedicated to pushing the boundaries of what's possible.
Learn more about NVIDIA Corporation
Size
22,473 employees
Market Cap
$350.4 billion
Industry
Manufacturing & Automotive
Net Income
$4.3 billion
Founded
1993
5 Year Trend
+31.3%
Revenue
$16.6 billion
NASDAQ
NVDA
* Ladders Estimates

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