Are you passionate about operating at internet scale? Do you want to work at the intersection of machine learning, data science, and causal inference? Are you eager to invent, grow, and learn alongside world-class engineers and scientists? If so, we want to hear from you! You will design and develop software products that deliver measurement data to a diverse set of users across Amazon's entire advertising suite. You'll demonstrate expertise in various architectural approaches and design patterns, with proven competence in building maintainable and scalable software using high-level languages. Collaborating with Data & Applied Scientists, Economists, and senior technical leaders who are advancing measurement science and causal inference, you'll adapt to evolving technical environments and devise creative solutions to complex software challenges. You'll tackle some of the most demanding and inspiring technical problems of your career—building petabyte-scale services, inventing new big data paradigms, and architecting for exponential growth. We measure advertising effectiveness through sophisticated causal measurement and modeling techniques, including rigorous scientific experiments and machine learning. Our mission is to enable advertisers to optimize ad spend and allocate budgets effectively by providing accurate, actionable, and timely causal measurement across all Amazon ad products. We combine deterministic and modeled measurement techniques to produce estimates that are fast, precise, and actionable. Using AWS big data and machine learning technologies, we process over 50 billion new events daily, operating petabyte-scale clusters. We continuously innovate on our event-driven architectures to stay ahead of rapidly growing scale. This team builds the core causal measurement and modeling capabilities serving all of Amazon Ads. We work with diverse systems and languages, combining AWS services like EMR and DynamoDB with Spark and Scala. We also leverage generative AI tools to accelerate our development, testing, and deployment cycles.
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Job Type
Full-time
Career Level
Mid Level