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2026 Fall Applied Science Internship - Information & Knowledge Management (Machine Learning) - United States, PhD Student Science Recruiting

Amazon.com Inc
  • Seattle, WA
    30+ days ago

    Job Description

    Unleash Your Potential at the Forefront of AI Innovation

    At Amazon, we"re on a mission to revolutionize the way the world leverages machine learning. Amazon is seeking graduate student scientists who can turn revolutionary theory into awe-inspiring reality. As an Applied Science Intern focused on Information and Knowledge Management in Machine Learning, you will play a critical role in developing the systems and frameworks that power Amazon"s machine learning capabilities. You"ll be at the epicenter of this transformation, shaping the systems and frameworks that power our cutting-edge AI capabilities.

    Imagine a role where you develop intuitive tools and workflows that empower machine learning teams to discover, reuse, and build upon existing models and datasets, accelerating innovation across the company. You"ll leverage natural language processing and information retrieval techniques to unlock insights from vast repositories of unstructured data, fueling the next generation of AI applications.

    Throughout your journey, you"ll have access to unparalleled resources, including state-of-the-art computing infrastructure, cutting-edge research papers, and mentorship from industry luminaries. This immersive experience will not only sharpen your technical skills but also cultivate your ability to think critically, communicate effectively, and thrive in a fast-paced, innovative environment where bold ideas are celebrated.

    Join us at the forefront of applied science, where your contributions will shape the future of AI and propel humanity forward. Seize this extraordinary opportunity to learn, grow, and leave an indelible mark on the world of technology.

    Amazon has positions available for Machine Learning Applied Science Internships in, but not limited to Arlington, VA; Bellevue, WA; Boston, MA; New York, NY; Palo Alto, CA; San Diego, CA; Santa Clara, CA; Seattle, WA.

    Key job responsibilities

    We are particularly interested in candidates with expertise in: Knowledge Graphs and Extraction, Neural Networks/GNNs, Data Structures and Algorithms, Time Series, Machine Learning, Natural Language Processing, Deep Learning, Large Language Models, Graph Modeling, Knowledge Graphs and Extraction, Programming/Scripting Languages

    In this role, you"ll collaborate with brilliant minds to develop innovative frameworks and tools that streamline the lifecycle of machine learning assets, from data to deployed models in areas at the intersection of Knowledge Management within Machine Learning. You will conduct groundbreaking research into emerging best practices and innovations in the field of ML operations, knowledge engineering, and information management, proposing novel approaches that could further enhance Amazon"s machine learning capabilities.

    The ideal candidate should possess the ability to work collaboratively with diverse groups and cross-functional teams to solve complex business problems. A successful candidate will be a self-starter, comfortable with ambiguity, with strong attention to detail and the ability to thrive in a fast-paced, ever-changing environment.

    A day in the life

    • Develop scalable, efficient, automated processes for large scale data analyses, model development, model validation and model implementation.
    • Design, development and evaluation of highly innovative ML models for solving complex business problems.
    • Research and apply the latest ML techniques and best practices from both academia and industry.
    • Think about customers and how to improve the customer delivery experience.
    • Use and analytical techniques to create scalable solutions for business problems.

    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

    Skills

    • Algorithmsunmatched
    • Analysis Skillsunmatched
    • Artificial Intelligence (AI)unmatched
    • Best Practicesunmatched
    • Communication Skillsunmatched
    • Cross-Functionalunmatched
    • Data Analysisunmatched
    • Data Modelingunmatched
    • Data Structuresunmatched
    • Deep Learningunmatched
    • Detail Orientedunmatched
    • Information Retrievalunmatched
    • Knowledge Engineeringunmatched
    • Knowledge Managementunmatched
    • Knowledge Modelingunmatched
    • Machine Learningunmatched
    • Model Validationunmatched
    • Modeling Languagesunmatched
    • Natural Language Processing (NLP)unmatched
    • Neural Networksunmatched
    • Problem Solving Skillsunmatched
    • Research Skillsunmatched
    • Scalable System Developmentunmatched
    • Scripting (Scripting Languages)unmatched
    • Team Playerunmatched
    • Training Data Setsunmatched
    • Unstructured Dataunmatched

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