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Machine Learning Engineer, Advertising & Marketing Performance Intelligence

Amazon.com Inc
  • Seattle, WA
    4 days ago

    Job Description

    The Advertising & Marketing Performance Intelligence (AMPI) team is seeking passionate and talented MLE to join us. Team is on a mission to

    create cohesive, relevant, and truly helpful marketing experiences for every advertiser through automated processes and intelligence that enable scaled personalization. Our team is responsible for defining and publishing automated marketing communications leveraging Machine Learning, large language models (LLMs), large quantitative models (LQMs), and specialized agents using AI/ML workflows.

    We are looking for a Machine Learning Engineer (MLE) to develop, deploy and scale robust ML and GenAI solutions in production environment. You will own building ML Infra for production models and feed AI/ML outputs to systems and services . In this role you will closely partner with Applied Scientists, Data Engineers,Product Managers, Software engineers to deliver and implement automated decision-making algorithms. This team plays a significant role in various stages of the innovation pipeline from identifying business needs, developing new algorithms, prototyping/simulation, to implementation by working closely with colleagues in engineering, science, product management, marketing business operations and finance.

    Key job responsibilities

    • Collaborate with Data and Applied Scientists to process structured/unstructured data inputs, scale ML and LLM infra while optimizing Infra costs, GPU utilization, memory management, and the training workflows (like offloading optimizer states, massive parallelization, etc) for the production environments.
    • Create and deliver reusable technical assets that help to accelerate the adoption of ML, Optimization and GenAI across different science initiatives
    • Design and maintain production grade large-scale distributed training systems to support ML, Causal, GenAI and multi-modal foundation models.
    • Optimize AWS AI/ML infra costs, GPU utilization for efficient model training, latency, costs and fine-tuning on massive datasets.
    • Develop robust monitoring and debugging tools to ensure the reliability and performance of training workflows, support piloting the LLMs and identify the related issues in the system.
    • Collaborate with Engineers, Data and Applied Scientists to investigate design approaches, prototype new GenAI and ML models, evaluate technical feasibility, identify and solve complex problems.

    A day in the life

    As a member of our team, you"ll work on projects that directly impact millions of Amazon advertisers and Marketers across the globe . This role will provide exposure to state-of-the-art innovations in Big Data, AI/ML systems and help Ads Marketing automate advertiser communications with personalized and relevant content and Measure/Calibrate Marketing effectiveness using RCTs. Technologies you will have exposure to, and/or will work with, include AWS Bedrock, Agentic AI (RAG, Agentic architectures, vector databases), Amazon Q, SageMaker, Containerized deployments, Hugging Face/LangChain, Guardrail implementations and Foundational Models such as Qwen, Anthropic's Claude / Mistral, among others.

    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

    • Advertisingunmatched
    • Algorithmsunmatched
    • Amazon Web Services (AWS)unmatched
    • Artificial Intelligence (AI)unmatched
    • Artificial Intelligence (AI) Agentsunmatched
    • Big Dataunmatched
    • Business Operationsunmatched
    • Cost Controlunmatched
    • Data Entryunmatched
    • Data Setsunmatched
    • Debugging Toolsunmatched
    • Distributed Computingunmatched
    • Feasibility Analysisunmatched
    • Financeunmatched
    • GPU (Graphics Processing Unit)unmatched
    • Identify Issuesunmatched
    • Large-Scale Systemsunmatched
    • Machine Learningunmatched
    • Marketingunmatched
    • Marketing Communicationsunmatched
    • Memory Managementunmatched
    • Modeling Languagesunmatched
    • Needs Assessmentunmatched
    • Problem Solving Skillsunmatched
    • Product Managementunmatched
    • Product Marketingunmatched
    • Production Systemsunmatched
    • Prototypingunmatched
    • Simulationunmatched
    • Software Engineeringunmatched
    • Structured Dataunmatched
    • Technical Analysisunmatched
    • Technical Deliveryunmatched
    • Unstructured Dataunmatched

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