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Manager, Applied Science, Sales AI

Amazon.com Inc

  • Seattle, WA
  • 3 days ago

    Highlights

    We are looking for a deeply scientific leader that brings their expertise in Natural Language Processing, Large Language Models, Reinforcement Learning, Deep learning and/or Recommender Systems to bring exciting new products come to life. Partner with business and technical stakeholders to define vision, priorities, and success criteria - ensuring your team builds the right solutions at the right level of fidelity and that final outputs are ready to inform business decisions or move to production.

    Numbers & Facts

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

    Description

    Are you excited about leading a team of scientists to solve complex, high-impact problems using machine learning and data-driven approaches? At Amazon Advertising Sales, we are looking for an experienced Applied Science Manager who can build, grow, and guide a team that delivers research and production-quality models at scale. In this role, you will own the strategic direction of your team"s scientific roadmap, partner closely with business and technical leaders, and ensure your team"s work directly shapes important decisions and customer-facing products. You will bridge the gap between science, technology, and business - translating ambiguous challenges into clear research agendas and actionable results. We are specifically looking to build AI agents that can operate accurately at large scale, helping transform the way account teams operate and optimize their end-to-end workflows. We are looking for a deeply scientific leader that brings their expertise in Natural Language Processing, Large Language Models, Reinforcement Learning, Deep learning and/or Recommender Systems to bring exciting new products come to life. If you are a thoughtful, collaborative leader who thrives on turning scientific innovation into measurable impact, we want to hear from you.

    Key job responsibilities

    • Lead and manage a team of applied scientists and analysts, setting the strategic direction and roadmap for scientific research that influences organizational goals and annual planning processes.
    • Partner with business and technical stakeholders to define vision, priorities, and success criteria - ensuring your team builds the right solutions at the right level of fidelity and that final outputs are ready to inform business decisions or move to production.
    • Evaluate and improve machine learning model accuracy and performance using rigorous experimentation, feature engineering, and hyperparameter optimization, while establishing a team culture focused on reproducibility and scientific rigor.
    • Hire, develop, and mentor scientists and technical contributors, providing growth opportunities and empowering team members to take ownership of key workstreams and deliver results independently.
    • Identify opportunities for new analysis, efficiency improvements, and generative AI integration, allocating resources effectively and proactively mitigating risks before they become roadblocks.

    A day in the life

    You start your morning reviewing experiment results with your scientists, asking probing questions about model assumptions and business relevance. Mid-morning, you join a cross-functional meeting with engineering and product partners to align on priorities for an upcoming launch. After lunch, you conduct a one-on-one with a team member, coaching them on a new research proposal. Later, you draft a narrative summarizing your team"s quarterly progress and outline next steps for leadership review. Throughout, you balance hands-on technical guidance with strategic planning to keep your team delivering high-quality science.

    About the team

    Sales AI is focused on applying scientific research and machine learning to solve real problems that matter to Amazon and its advertising customers. We value intellectual curiosity, collaboration, and a commitment to building inclusive, high-performing teams. We believe that great science happens when people with different perspectives work together toward a shared mission. As we continue to grow, you will play a key role in shaping the team"s direction, expanding our capabilities, and ensuring our work has lasting impact across the business.

    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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