Senior Architecture Energy Modeling Engineer

Job Title

Senior Architecture Energy Modeling Engineer

Role Summary

Develop energy and power models for GPUs and SoCs using machine learning and statistical methods, and integrate those models into architectural simulators, RTL/emulation, and silicon to influence architecture, design, and power management decisions.

Work cross-functionally with architects, ASIC designers, performance and software teams to provide early insight into energy consumption and recommend improvements.

Experience Level

Senior-level; typically requires 5+ years of relevant experience.

Responsibilities

Key responsibilities include building models and tools, integrating them into platforms, and using them to locate and mitigate energy inefficiencies.

• Collaborate with architects, designers, and performance engineers to improve GPU energy efficiency.
• Identify design features and workloads for ML-based unit power/energy models.
• Develop methodologies and workflows to train and validate ML/statistical power models.
• Improve model accuracy through different representations, objective functions, and learning algorithms.
• Estimate data-movement power/energy and correlate model predictions across design stages to silicon.
• Integrate power/energy models into performance infrastructure for combined reporting.
• Develop tools to debug energy inefficiencies on silicon, RTL, and simulators and recommend fixes.
• Prototype architectural features and analyze their system-level energy impact.

Requirements

Concise list of required skills and preferred qualifications.

• Must-have: Strong programming skills, preferably Python and C++.
• Must-have: Background in machine learning, AI, or statistical modeling.
• Must-have: Experience with computer architecture and interest in energy-efficient GPU design.
• Must-have: Ability to formulate and analyze algorithms, including runtime and memory complexity.
• Must-have: Basic understanding of energy consumption, estimation, and low-power design.
• Must-have: Good verbal and written communication skills.
• Nice-to-have: Familiarity with Verilog and ASIC design principles.

Education Requirements

MS or PhD in Electrical Engineering, Computer Engineering, Computer Science, 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.