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Senior Applied Scientist, Kumo

Amazon.com Inc
  • Bellevue, WA
    18 days ago

    Job Description

    At AWS, we use Artificial Intelligence to be able to identify every need of a customer across all AWS services before they have to tell us about it and help customers adopt best practices while architecting on the cloud. We are looking for a Senior Applied scientist who will function as a science leader and drive innovation with Gen AI to bring paradigm shift to how the business operates and build "best in the world" experience that customers will love!

    As part of the AWS Applied AI Solutions organization, we have a vision to provide business applications, leveraging Amazon"s unique experience and expertise, that are used by millions of companies worldwide to manage day-to-day operations. We will accomplish this by accelerating our customers" businesses through delivery of intuitive and differentiated technology solutions that solve enduring business challenges. We blend vision with curiosity and Amazon"s real-world experience to build opinionated, turnkey solutions. Where customers prefer to buy over build, we become their trusted partner with solutions that are no-brainers to buy and easy to use.

    Some of the science challenges we work on include building Agentic AI systems for complex use cases such as optimizing customers' cloud architectures, innovating optimization techniques for cost-efficiency in agentic workflows, fine-tuning language models for domain specific use cases, building scalable agentic evaluation systems, designing continual learning systems that incorporate real-time customer and operational feedback to improve model performance over time and developing collaborative filtering approaches that surface personalized recommendations at scale.

    You will have an opportunity to lead, invent, and design technology that will directly impact every customer across all AWS services. We are building industry-leading technology that cuts across a wide range of ML techniques from Natural Language Processing to Deep Learning and Generative Artificial Intelligence. You will be a key driver in taking something from an idea to an experiment to a prototype and finally to a live production system.

    As a senior scientist on this team, you will define the science vision and long-term research roadmap for your problem space. You will set technical and research direction and ensure our approaches remain at the frontier of what"s possible. You will mentor junior scientists and engineers, helping them grow their technical depth, develop scientific rigor, and navigate ambiguous problem spaces. You will raise the bar for the team through code reviews, science experimentation reviews, and by fostering a culture of experimentation and intellectual curiosity.

    Key job responsibilities

    • Deliver real world production systems at AWS scale.
    • Work closely with the business to understand the problem space, identify the opportunities and formulate the problems.
    • Use machine learning, data mining, statistical techniques, Generative AI and others to create actionable, meaningful, and scalable solutions for the business problems.
    • Analyze and extract relevant information from large amounts of data and derive useful insights.
    • Work with software engineering teams to deliver production systems with your ML models
    • Establish scalable, efficient, automated processes for large scale data analyses, model development, model validation and model implementation

    A day in the life

    Diverse Experiences

    AWS values diverse experiences. Even if you do not meet all of the qualifications and skills listed in the job description, we encourage candidates to apply. If your career is just starting, hasn't followed a traditional path, or includes alternative experiences, don't let it stop you from applying.

    Why AWS?

    Amazon Web Services (AWS) is the world's most comprehensive and broadly adopted cloud platform. We pioneered cloud computing and never stopped innovating - that's why customers from the most successful startups to Global 500 companies trust our robust suite of products and services to power their businesses.

    Inclusive Team Culture

    Here at AWS, it's in our nature to learn and be curious. Our employee-led affinity groups foster a culture of inclusion that empower us to be proud of our differences. Ongoing events and learning experiences, including our Conversations on Race and Ethnicity (CORE) and AmazeCon (gender diversity) conferences, inspire us to never stop embracing our uniqueness.

    Mentorship & Career Growth

    We're continuously raising our performance bar as we strive to become Earth's Best Employer. That's why you'll find endless knowledge-sharing, mentorship and other career-advancing resources here to help you develop into a better-rounded professional.

    Work/Life Balance

    We value work-life harmony. Achieving success at work should never come at the expense of sacrifices at home, which is why we strive for flexibility as part of our working culture. When we feel supported in the workplace and at home, there's nothing we can't achieve in the cloud.

    Hybrid Work

    We value innovation and recognize this sometimes requires uninterrupted time to focus on a build. We also value in-person collaboration and time spent face-to-face. Our team affords employees options to work in the office every day or in a flexible, hybrid work model near one of our U.S. Amazon offices.

    Numbers & Facts

    LocationBellevue, 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

    • Amazon Web Services (AWS)unmatched
    • Analysis Skillsunmatched
    • Artificial Intelligence (AI)unmatched
    • Best Practicesunmatched
    • Business Solutionsunmatched
    • Cloud Architectureunmatched
    • Cloud Computingunmatched
    • Code Reviewsunmatched
    • Constructionunmatched
    • Cost Controlunmatched
    • Customer Acquisitionunmatched
    • Customer Support/Serviceunmatched
    • Data Miningunmatched
    • Deep Learningunmatched
    • Identify Issuesunmatched
    • Machine Learningunmatched
    • Mentoringunmatched
    • Modeling Languagesunmatched
    • Natural Language Processing (NLP)unmatched
    • Operational Improvementunmatched
    • Performance Managementunmatched
    • Performance Modelingunmatched
    • Production Systemsunmatched
    • Prototypingunmatched
    • Scalable System Developmentunmatched
    • Software Engineeringunmatched
    • Startupunmatched
    • Statisticsunmatched
    • Team Playerunmatched
    • Technical Leadershipunmatched
    • Technical Researchunmatched
    • Use Casesunmatched

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