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

Amazon Amazon · Big Tech · Seattle, WA · Software Development

Software Development Engineer for Prime Video Personalization & Discovery Growth team, focusing on building and operating scalable measurement, attribution, and audience optimization systems that leverage AI/ML to connect customers with content and drive subscriber growth. The role involves designing and building services, data pipelines, integrating ML models, and impacting decisions for over 200M customers.

What you'd actually do

  1. 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
  2. Lead high-impact projects from design through production, making sound technical trade-offs and delivering results
  3. Build data pipelines that ingest, process, and serve campaign performance data at scale
  4. Integrate ML models into production services, including feature engineering, inference, and monitoring
  5. Partner with engineers, scientists, product managers, and marketing teams to translate business needs into technical solutions

Skills

Required

  • 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

Nice to have

  • 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)

What the JD emphasized

  • directly impact how Prime Video invests marketing dollars
  • directly impact millions of customers
  • directly impact millions of people globally

Other signals

  • Connect customers with their favorite Movies, TV shows, and Live Events
  • power highly personalized recommendations
  • identify the most delightful content for each customer
  • build scalable measurement, attribution, and audience optimization systems
  • measure campaign effectiveness
  • generate attribution insights
  • build audience models that optimize targeting and performance at scale
  • leverage models for lift measurement, incrementality testing, and audience optimization
  • AWS clean room infrastructure
  • lift and incrementality measurement
  • data pipeline engineering
  • influencing decisions that reach 200M+ customers worldwide
  • build systems that prove what works in advertising and media performance at scale
  • ship features that directly impact millions of customers
  • Experiment with new technologies
  • own the full stack, from distributed services to ML models
  • 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
  • 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
  • measure, attribute, and optimize Prime Video's marketing investments across paid media, social platforms, and connected TV
  • build solutions that power audience targeting, measurement, attribution, optimization, and content discovery across various platforms
  • data-driven approach, constantly analyzing performance and iterating on our solutions to deliver the best possible customer experience