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Software Engineer - Hardware Abstraction Layer, AWS Machine Learning Accelerators

Amazon.com Inc

  • Cupertino, CA
  • 3 days ago

    Highlights

    Enjoy learning new technologies, building software at scale, moving fast, and working closely with colleagues as part of a small, startup-like team within a large organization. We're looking for engineers to scale the system software team developing the hardware abstraction layer (HAL) that manages these cutting-edge ML system-on-chips (SoCs).

    Numbers & Facts

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

    Description

    Custom silicon chips live at the heart of AWS machine learning servers (Trainium and Inferentia), and enable machine learning (ML) for AWS"s customers. We're looking for engineers to scale the system software team developing the hardware abstraction layer (HAL) that manages these cutting-edge ML system-on-chips (SoCs). The HAL forms the lowest level of the AWS infrastructure management software stack.

    As a software engineer developing the SoC HAL, you will:

    • Work with hardware designers to build HALs for newly developed SoC IPs
    • Work with system software teams to solve SoC and system-level architectural issues, drive debug, architect the HAL itself, and innovate on cross-functional solutions
    • Continuously test and deploy your software stack to multiple internal customers
    • Refactor and maintain existing codebases throughout the device lifecycle
    • Innovate on the tooling you provide to customers, making it easier for them to use our SoCs

    AWS"s Annapurna Labs organization designs and deploys some of the largest custom silicon in the world, with many subsystems that must all be managed, tested, and monitored. The SoC HAL is a critical piece of the AWS infrastructure management software stack that ensure the chip is functional, performant, and secure.

    You will thrive in this role if you:

    • Are strong in C++ and familiar with Python
    • Enjoy working with hardware-based systems, and diving into chip and system architecture
    • Know how to build effective abstractions over low-level SoC details
    • Have strong opinions about software architecture, and are able to apply them effectively
    • Are familiar with modular driver architectures (such as the Linux or Windows device-driver stacks)
    • Enjoy learning new technologies, building software at scale, moving fast, and working closely with colleagues as part of a small, startup-like team within a large organization

    Although we build and deploy ML chips, no ML background is needed for this role. You (and your software) won't be doing ML. Our HAL lives at the lowest level of the backend AWS infrastructure responsible for managing our ML servers. You and your team will develop HALs for components used by machine learning, like PCIe and HBM, but won't need to deeply understand ML yourselves.

    This role can be based in either Cupertino, CA or Austin, TX. The team is split between the two sites, with no preference for one over the other.

    This is a fast-paced role where you"ll work with thought-leaders in multiple technology areas. You"ll have high standards for yourself and everyone you work with, and you"ll be constantly looking for ways to improve your software, as well as our products" overall performance, quality, and cost.

    We"re changing an industry. We"re searching for individuals who are ready for this challenge, who want to reach beyond what is possible today. Come join us and build the future of machine learning!

    A day in the life

    A few videos help explain what the Annapurna Labs ML team is working on:

    About the team

    Annapurna Labs, designs custom silicon powering AWS's cloud infrastructure. Custom SoCs live at the heart of Amazon ML servers - including Inferentia and Trainium Systems - delivering high-performance ML inference and training at cloud scale.

    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.

    It’s Always Day 1
    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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