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Software Development Engineer - Maching Learning, Prime Video Personalization and Discovery Growth

Amazon

Seattle, WA

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JOB DETAILS
SKILLS
Advertising, Amazon Web Services (AWS), Apache Hadoop, Apache Hive, Apache Lucene, Apache Pig, Apache Spark, Artificial Intelligence (AI), Best Practices, Big Data, Building Systems, Campaigns, Clean Technologies, Cleanroom, Code Reviews, Coding Standards, Computer Science, Content Management, Customer Experience, Data Management, Data Processing, Data Science, Design Patterns Programming Methodologies, Distributed Computing, Film, Football, Housekeeping/Cleaning, Machine Learning, Marketing, Marketing Software, Mathematics, Mentoring, Modeling Languages, Multiplatform/Cross-Platform, Needs Assessment, Performance Analysis, Performance Tuning/Optimization, Product Marketing, Project Design, SOLR, Scalable System Development, Social Media, Software Development, Software Development Lifecycle (SDLC), Software Engineering, Source Code/Configuration Management (SCM), Team Lead/Manager, Team Player, Testing, Video Production
LOCATION
Seattle, WA
POSTED
1 day ago
Description Ever wondered how streaming platforms know which ad drove you to watch your next favorite show? We're building the systems that answer that question at scale. Prime Video Personalization & Discovery Growth team leverages AI and Machine Learning systems to connect customers with their favorite Movies, TV shows, and Live Events. We power highly personalized recommendations, identify the most delightful content for each customer to engage with at the right time, in the right place, across Prime Video and social media platforms. We are seeking a Software Development Engineer to build scalable measurement, attribution, and audience optimization systems that directly impact how Prime Video invests marketing dollars, improves content discovery for customers, and drives subscriber growth. You will design and operate services that measure campaign effectiveness, generate attribution insights, and build audience models that optimize targeting and performance at scale. Experience with ML is valued as our systems leverage models for lift measurement, incrementality testing, and audience optimization. Your work will span AWS clean room infrastructure, lift and incrementality measurement, and data pipeline engineering, influencing decisions that reach 200M+ customers worldwide. If you're a customer-obsessed engineer with a strong computer science foundation, experience in ML systems, and a passion for building systems that prove what works in advertising and media performance at scale, this is your chance to make a difference. You'll own critical systems end-to-end, tackle complex engineering challenges across distributed systems, ML infrastructure, and large-scale data processing, and ship features that directly impact millions of customers. Experiment with new technologies. Collaborate with engineers, scientists, marketing managers, and external partners. We'll look for you to bring your diverse perspectives, ideas, and skill-sets to make Prime Video even better for our customers. With global opportunities for talented technologists, you can decide where a career in Prime Video Tech takes you! Key job responsibilities - Design and build scalable services that power marketing measurement, attribution, and audience optimization across paid media channels, driving content discovery and subscriber growth for Prime Video - Lead high-impact projects from design through production, making sound technical trade-offs and delivering results - Build data pipelines that ingest, process, and serve campaign performance data at scale - Integrate ML models into production services, including feature engineering, inference, and monitoring - Partner with engineers, scientists, product managers, and marketing teams to translate business needs into technical solutions - Champion code quality, operational excellence, and engineering best practices through code reviews and mentorship A day in the life Build bleeding-edge solutions for marketing measurement, audience targeting, optimization, and campaign performance across paid media and social platforms. Harness machine learning to understand customer needs and connect them with content they love. Collaborate with marketing, data science, and engineering teams to research and build new channels for customer engagement. Own the full stack, from distributed services to ML models, with a wide variety of projects and technical challenges. Make a real impact on a product used by millions of people globally. Work on industry-defining content like Lord of the Rings, Thursday Night Football, and Jack Ryan. Enjoy a dynamic environment with talented colleagues and supportive managers. Grow your career, skills, and expand your impact About the team Be a part of a dynamic and collaborative team at the forefront of innovation in the streaming industry! We leverage bleeding-edge technology, including Machine Learning and AI, to measure, attribute, and optimize Prime Video's marketing investments across paid media, social platforms, and connected TV. We work closely with marketing, data science, and engineering teams to build solutions that power audience targeting, measurement, attribution, optimization, and content discovery across various platforms. We're a self-managed team, operating with a high degree of independence and ownership. From day one, your manager will work closely with you to support your career growth and help you achieve your professional goals. We embrace a data-driven approach, constantly analyzing performance and iterating on our solutions to deliver the best possible customer experience. We're a tight-knit group that thrives on mutual respect, continuous learning, and a shared passion for pushing the boundaries of entertainment technology. Basic Qualifications - Bachelor's degree or foreign equivalent in Computer Science, Engineering, Mathematics, or a related field - 3+ years of non-internship professional software development experience - 2+ years of non-internship design or architecture (design patterns, reliability and scaling) of new and existing systems experience - 2+ years of big data technologies such as AWS, Hadoop, Spark, Pig, Hive, Lucene/SOLR or Storm/Samza experience Preferred Qualifications - 3+ years of full software development life cycle, including coding standards, code reviews, source control management, build processes, testing, and operations experience - Experience with Machine Learning and Large Language Model fundamentals, including architecture, training/inference lifecycles, and optimization of model execution - Experience with ad-tech measurement, attribution methodologies, or clean room technologies (e.g., AWS Clean Rooms) Amazon is an equal opportunity employer and does not discriminate on the basis of protected veteran status, disability, or other legally protected status. Our inclusive culture empowers Amazonians to deliver the best results for our customers. If you have a disability and need a workplace accommodation or adjustment during the application and hiring process, including support for the interview or onboarding process, please visit https://amazon.jobs/content/en/how-we-hire/accommodations for more information. If the country/region you're applying in isn't listed, please contact your Recruiting Partner. The base salary range for this position is listed below. Your Amazon package will include sign-on payments and restricted stock units (RSUs). Final compensation will be determined based on factors including experience, qualifications, and location. Amazon also offers comprehensive benefits including health insurance (medical, dental, vision, prescription, Basic Life & AD&D insurance and option for Supplemental life plans, EAP, Mental Health Support, Medical Advice Line, Flexible Spending Accounts, Adoption and Surrogacy Reimbursement coverage), 401(k) matching, paid time off, and parental leave. Learn more about our benefits at https://amazon.jobs/en/benefits . USA, WA, SEATTLE - 143,700.00 - 194,400.00 USD annually

About the Company

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Amazon

INDUSTRY
Other/Not Classified

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