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NVIDIA

Designs the chips and software that power AI

Power Methodology and Modeling Engineer New Grad

Hardware EngineeringConfirmed live in the last 24 hours
Full-timeAustin, TX, USAIn-person

About the Job

Requirements

  • Pursuing or recently completed a Master of Science or PhD in Electrical or Computer Engineering, or equivalent experience.
  • Strong coding skills, preferably in Python or C++.
  • Ability to formulate and analyze algorithms and assess their runtime and memory complexity.
  • Understanding of very-large-scale integration, digital design, and computer architecture concepts.
  • Basic understanding of power and energy consumption, estimation, and low-power design.
  • Basic understanding of the chip design process from register-transfer-level design to tape-out.
  • Background in machine learning, artificial intelligence, and/or statistical modeling is a plus.
  • Desire to apply quantitative decision-making and analytics to improve product energy efficiency.

Responsibilities

  • Define and implement tools and methodologies for efficient data generation from post-layout netlists to feed a data-movement power analytical model.
  • Develop tools and infrastructure to sanitize each model metric to achieve high correlation accuracy.
  • Define and implement tools and methodologies for efficient integration of power models with performance tools.
  • Identify runtime and memory limitations of existing flows and tools to speed up model delivery.
  • Mine data from pre- and post-silicon performance runs to identify important data paths and bottlenecks, provide 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 machine learning techniques to answer what-if design questions and set power and energy targets for next-generation chips.
  • Enable efficient storage and retrieval of data from a database.
  • Enable easy data visualization using platforms such as Power BI and OpenSearch.

About the Company

NVIDIA

Designs the chips and software that power AI

NVIDIA designs the chips and software that power artificial intelligence and sells complete data center systems to cloud providers, AI labs, and other businesses, along with GeForce graphics cards for gamers. Its GPUs, chips that perform thousands of calculations at once, became the main hardware for AI after researchers used them to train the AlexNet image-recognition model in 2012. NVIDIA connects many GPUs with its own processors and networking gear into servers and rack-sized computers, and developers program them through its CUDA software. These systems bring in most of its sales, and it also makes chips for cars and robots. Jensen Huang co-founded NVIDIA in 1993, and it is based in Santa Clara, California.

Company size
10,001+
Company stage
IPO
Headquarters
Santa Clara, CA
Founded
1993

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