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Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Architecture Energy Modeling Engineer - New College Grad 2026 - **Company:** NVIDIA Ltd. - **Location:** Santa Clara, CA, United States - **Experience:** Starter - **Salary:** $62,400.0 - $112,320.0 - **Contract:** Permanent contract - **Skills:** Artificial Intelligence, C++ (Programming Language), Computer Engineering, Extract Transform Load (ETL), Software Debugging, Python (Programming Language), Machine Learning, Verilog, Application Specific Integrated Circuits, Information Technology, Modeling and Simulation, Software Coding - **Published:** August 23, 2026 - **Apply:** https://www.jofdav.com/jobs/59370673-architecture-energy-modeling-engineer-new-college-grad-2026 ## About the Role * 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. ## Description * 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. ## Related Videos - [Introduction to Azure Machine Learning](https://www.wearedevelopers.com/videos/368-introduction-to-azure-machine-learning) - [Unleashing the Power of Developers: Why Cybersecurity is the Missing Piece?!?](https://www.wearedevelopers.com/videos/712-unleashing-the-power-of-developers-why-cybersecurity-is-the-missing-piece) - [Your Next AI Needs 10,000 GPUs. 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