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Sr. SoC Power Engineer, Annapurna Labs - Cloud Scale Machine Learning

Amazon.com Inc

  • Cupertino, CA
  • 30+ days ago

    Highlights

    SoC Power Engineer, you'll contribute to the project at the ground level by modeling and estimating power at every stage of the design from early RTL to final netlist and by driving ways to reduce power consumption of our machine learning accelerators. In this role, you'll be working directly with architects, designers, verification engineers, software teams, and Physical Design experts - defining best practices to reduce power and model power consumption with high accuracy.

    Numbers & Facts

    LocationCupertino, CA
    IndustryRetail
    Company Size10,000 employees or more
    Year Founded1994
    Websitehttp://Amazon.com/militaryroles

    Description

    Our Machine Learning Acceleration (MLA) team develops the Inferentia and Trainium SoCs that are used to power today's AI workloads in datacenters all around the world. As a Sr. SoC Power Engineer, you'll contribute to the project at the ground level by modeling and estimating power at every stage of the design from early RTL to final netlist and by driving ways to reduce power consumption of our machine learning accelerators.

    We're searching for an experienced SoC Power engineer with a background in Power analysis with a proven track record of handling challenges at scale. In this role, you'll be working directly with architects, designers, verification engineers, software teams, and Physical Design experts - defining best practices to reduce power and model power consumption with high accuracy.

    Key job responsibilities

    • Responsible for full chip power analysis & modelling at various stages of design (RTL to gate level netlist)
    • Develop and maintain dashboards for power rollups
    • Work with designers, architects, Verification engineers and Physical Design engineers to develop vectors for IR analysis, Thermal analysis and power estimation
    • Give feedback to designers and architects on how to reduce power
    • Make power measurements in the lab and correlate back to simulations.
    • Work with Emulation engineers to model chip-level power consumption

    About Company

    At Amazon, we don’t wait for the next big idea to present itself. We envision the shape of impossible things and then we boldly make them reality. So far, this mindset has helped us achieve some incredible things. Let’s build new systems, challenge the status quo, and design the world we want to live in. We believe the work you do here will be the best work of your life.

    Wherever you are in your career exploration, Amazon likely has an opportunity for you. Our research scientists and engineers shape the future of natural language understanding with Alexa. Fulfillment center associates around the globe send customer orders from our warehouses to doorsteps. Product managers set feature requirements, strategy, and marketing messages for brand new customer experiences. And as we grow, we’ll add jobs that haven’t been invented yet.

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    At Amazon, it’s always “Day 1.” Now, what does this mean and why does it matter? It means that our approach remains the same as it was on Amazon’s very first day – to make smart, fast decisions, stay nimble, invent, and stay focused on delighting our customers. In our 2016 shareholder letter, Amazon CEO Jeff Bezos shared his thoughts on how to keep up a Day 1 company mindset. “Staying in Day 1 requires you to experiment patiently, accept failures, plant seeds, protect saplings, and double down when you see customer delight,” he wrote. “A customer-obsessed culture best creates the conditions where all of that can happen.” You can read the full letter here

    Our Leadership Principles
    Our Leadership Principles help us keep a Day 1 mentality. They aren’t just a pretty inspirational wall hanging. Amazonians use them, every day, whether they’re discussing ideas for new projects, deciding on the best solution for a customer’s problem, or interviewing candidates. To read through our Leadership Principles from Customer Obsession to Bias for Action, visit https://www.amazon.jobs/principles

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