Senior Architecture Energy Modeling Engineer

Job Title

Senior Architecture Energy Modeling Engineer

Role Summary

The Senior Architecture Energy Modeling Engineer develops and deploys methodologies and energy models to analyze and reduce power and energy consumption across GPUs, CPUs, and SoCs. The role focuses on building ML- and statistics-based power/energy models and integrating them into architectural simulators, RTL/emulation, and silicon platforms.

Works closely with architects, ASIC designers, low-power, performance, software, and physical design teams to influence architectural and power-management decisions.

Experience Level

Senior — typically requires 5+ years of relevant experience.

Responsibilities

Key responsibilities include:

• Develop ML- and statistical-based unit power/energy models for GPU components and system features.
• Create methodologies and workflows to train, validate, and improve models using different representations, objectives, and learning algorithms.
• Estimate data-movement power/energy accurately and correlate model predictions across design stages (architecture, RTL, silicon).
• Integrate power/energy models into performance and architectural platforms for combined reporting.
• Develop tools and methods to debug energy inefficiencies observed on silicon, RTL, and simulators and propose remediation strategies.
• Prototype new architectural features, model their energy impact, and analyze system-level perf/watt tradeoffs.
• Collaborate with cross-functional teams to identify features and workloads for modeling and to influence design decisions.

Requirements

Must-have technical skills and experience:

• 5+ years of relevant engineering experience in power/energy modeling, architecture, or related fields.
• Strong programming skills, preferably Python and C++.
• Experience with machine learning, AI, or statistical modeling applied to system or component-level estimation.
• Background in computer architecture and interest in energy-efficient GPU design.
• Ability to formulate and analyze algorithms, including runtime and memory complexity considerations.
• Basic understanding of energy consumption, estimation techniques, and low-power design concepts.
• Good verbal and written communication and interpersonal skills.
• Nice-to-have: familiarity with Verilog and ASIC design principles.

Education Requirements

MS or PhD in Electrical Engineering, Computer Engineering, Computer Science, or a closely related field, or equivalent practical experience.

About the Company

Company: NVIDIA

Headquarters: Santa Clara, California, USA

NVIDIA is a global leader in accelerated computing, renowned for its innovative solutions in AI and digital twins that transform diverse industries. The company specializes in networking technologies, providing end-to-end InfiniBand and Ethernet solutions for servers and storage that optimize performance and scalability. NVIDIA serves sectors such as high-performance computing, enterprise data centers, and cloud computing, constantly reinventing its products and services to stay ahead in the market.