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Applied Scientist, AWS Applied AI Solutions Core Services

Amazon.com Inc

  • Seattle, WA
  • 10 days ago
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    Skills

    • Algorithmsunmatched
    • Amazon Web Services (AWS)unmatched
    • Artificial Intelligence (AI)unmatched
    • Automationunmatched
    • Best Practicesunmatched
    • Business Caseunmatched
    • Computer Visionunmatched
    • Develop Methodologiesunmatched
    • Geospatial Intelligence (GEOINT)unmatched
    • Internet of Thingsunmatched
    • Machine Learningunmatched
    • Mentoringunmatched
    • Modeling Languagesunmatched
    • Physicsunmatched
    • Product Supportunmatched
    • Production Systemsunmatched
    • Proof of Conceptunmatched
    • Safety Systemsunmatched
    • Scientific Publicationsunmatched
    • System Architectureunmatched
    • System Operationsunmatched
    • Team Playerunmatched
    • Use Casesunmatched
    • Video Processingunmatched

    Description

    As part of the AWS Applied AI Solutions organization, we"re building the future of AI-powered enterprise services across multiple domains. Our vision is to be the trusted foundation for transforming every business with Amazon AI teammates. Our mission is to deliver turnkey, enterprise-grade foundational AI capabilities that create delightful AI powered solutions. We"re developing sophisticated AI systems that address complex challenges across autonomous operations, geospatial intelligence, trust and safety, IoT services, and foundational AI platforms.

    Key job responsibilities

    • Develop and productize AI solutions that address complex technical challenges requiring novel approaches beyond off-the-shelf tools
    • Design and implement machine learning systems for diverse applications including video understanding, geospatial optimization, fraud detection, anomaly detection, and automation
    • Create scalable algorithms and models that generalize across multiple customer use cases and business problems
    • Conduct rigorous experimentation with state-of-the-art techniques including large language models, computer vision, federated learning, or physics-based modeling, and agentic AI systems
    • Collaborate with engineering teams to integrate science components into production systems with measurable customer impact
    • Work directly with product teams to understand requirements, frame ambiguous problems into tractable science solutions, and validate approaches through proof of concepts
    • Establish evaluation frameworks and best practices for measuring solution performance and business impact
    • Mentor other scientists and contribute to the broader scientific community through publications when appropriate

    A day in the life

    As an Applied Scientist, you"ll work on challenging problems that span multiple domains within AWS Core Services. You might develop video processing architectures for autonomous systems, create optimization solvers for geospatial applications, build behavioral detection models for fraud prevention, design anomaly detection systems for IoT devices, or develop specialized AI capabilities for platform services. You"ll investigate novel approaches, validate ideas through rigorous experimentation with real data, and collaborate with scientists and engineers to transform research insights into scalable solutions.

    About the team

    Our team is a central science organization supporting multiple product teams across AWS Core Services. We tackle fundamental challenges in AI and machine learning that require novel approaches beyond off-the-shelf solutions. Working at the intersection of machine learning, large language models, and domain-specific applications, we develop practical techniques that advance the state-of-the-art while maintaining a clear path to customer impact. Our team builds deep domain expertise across geospatial intelligence, trust and safety systems, autonomous operations, and other critical areas, collaborating closely with engineering teams to transform research insights into scalable production solutions.

    Numbers & Facts

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

    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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