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Software Dev Engineer, EC2 Nitro

Amazon.com Inc

  • Seattle, WA
  • 30+ days ago

    Highlights

    Your impact will extend from low-level systems (CUDA, EFA, firmware) through ML frameworks to serving layers, requiring deep technical knowledge and the ability to communicate complex performance data as actionable business insights. Your expertise will directly influence future platform designs by translating performance insights from state of the art research and customer workloads into technical requirements for upcoming accelerated platform launches.

    Numbers & Facts

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

    Description

    Join the EC2 Nitro Machine Learning Systems team to revolutionize accelerated computing in the cloud. Were seeking an exceptional Software Development Engineer to build and optimize the performance measurement infrastructure for some of the most computationally intensive AI/ML workloads on AWS.

    In this role, youll establish EC2 as the definitive source for best-known-configurations across diverse ML applications including LLMs, multimodal models, and video generation workloads. Your expertise will directly influence future platform designs by translating performance insights from state of the art research and customer workloads into technical requirements for upcoming accelerated platform launches.

    Your impact will extend from low-level systems (CUDA, EFA, firmware) through ML frameworks to serving layers, requiring deep technical knowledge and the ability to communicate complex performance data as actionable business insights. This position offers the unique opportunity to shape the future of machine learning infrastructure at cloud scale while working at the intersection of high-performance computing, distributed systems, and machine learning technologies.

    Key Job Responsibilities:

    • Design and build foundational infrastructure for ML performance measurement that scales with business demand and operates as reliable CI/CD systems, ensuring high-quality implementations that balance customer requirements with operational excellence
    • Develop comprehensive regression test coverage across all major component releases including frameworks, firmware, drivers, and networking technologies to maintain optimal platform performance
    • Collaborate with cross-functional teams to establish EC2 as the definitive source for best-known-configurations across diverse ML applications including LLMs, multimodal models, and MoE architectures
    • Document and communicate performance insights to influence future platform designs by translating technical findings from research and customer workloads into actionable recommendations
    • Identify and resolve complex performance challenges through systematic analysis of training and inference performance KPIs across accelerated platforms, working directly with customers to improve their ML system efficiency

    A Day in the Life:

    Your typical day begins with reviewing performance data from overnight benchmark runs across various ML frameworks and hardware configurations. Youll investigate anomalies, collaborate with the team on optimization opportunities, and join design reviews to influence future platform capabilities. Youll balance your time between building measurement infrastructure, analyzing performance trends, and documenting best practices to help customers optimize their workloads.

    About the Team:

    The EC2 Nitro Machine Learning Systems team is responsible for development, operations, and maintenance of scale-out machine learning platforms used for training and inference workloads. We build and optimize the infrastructure that powers some of the most computationally intensive AI/ML workloads in the cloud.

    Our team is passionate about creating reliable, high-performance systems that enable customers to push the boundaries of whats possible with machine learning. Working with us means having the opportunity to influence the future of supercomputing in the cloud while solving complex technical challenges at massive scale. We collaborate closely with customers and internal teams to continuously improve our platforms and deliver innovations that accelerate machine learning workflows.

    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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