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Power Methodology and Modeling Engineer - New College Grad 2026

NVIDIA· Engineer, ASIC
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Austin, TX$116k - $189.8kfull-timePosted 5mo ago

About the role

Energy modeling-focused engineering role within NVIDIA's Architecture Energy Modeling Team, collaborating across design and methodology groups to study and implement power/energy modeling techniques for GPUs, CPUs, and Tegra SOCs; includes data generation, model integration, ML experimentation, and data visualization.

Responsibilities

  • - Define and implement tools and methodologies for efficient data generation from post layout netlists to feed into data movement power analytical model.
  • - Develop tools and infrastructure to sanitize each metric in the model to achieve high correlation accuracy.
  • - Define and implement tools and methodologies for efficient integration of power models with performance tools.
  • - Identify runtime and memory limitation of existing flows and tools to speedup model delivery process.
  • - Mine data from pre- and post-silicon performance runs to find important data paths and bottlenecks. Give feedback to design teams and improve power efficiency.
  • - Work with floorplan, performance, verification and emulation methodology and infrastructure development teams to integrate data movement power models.
  • - Experiment with various ML techniques to answer what-if design questions and set proper power/energy targets for next generation chips.
  • - Enable efficient storage and retrieval of data from database.
  • - Enable easy visualization of data using platforms such as PowerBI, OpenSearch.

Qualifications

  • - Pursuing or recently completed a MS or PhD in Electrical or Computer Engineering or equivalent experience.
  • - Strong coding skills, preferably in Python, C++.
  • - Ability to formulate and analyze algorithms, and comment on their runtime and memory complexities.
  • - Understanding of VLSI, digital design, and computer architecture concepts.
  • - Basic understanding of fundamental concepts of power and energy consumption, estimation, and low power design.
  • - Basic understanding of chip design process from RTL design to tape-out.
  • - Background in machine learning, AI, and/or statistical modeling is a plus.
  • - Desire to bring quantitative decision-making and analytics to improve the energy efficiency of our products.

Skills

Required:PythonC++Algorithm analysisVLSI / digital design / computer architecture

Benefits

  • - equity
  • - benefits (as referenced in the posting)
Last updated Jul 3, 2026. Interested? Apply on the company site.

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