Software Development Engineer, Measurement, Ad Tech, and Data Science (MADS)

About the role

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.

Requirements

• 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
• 1+ years of designing and developing large-scale, multi-tiered, multi-threaded, embedded or distributed software applications, tools, systems, and services using: C#, C++, Java, or Perl experience
• 1+ years of Object Oriented Design experience
• Experience programming with at least one software programming language
• 3+ years of full software development life cycle, including coding standards, code reviews, source control management, build processes, testing, and operations experience
• Bachelor's degree in computer science or equivalent
• Amazon is an equal opportunity employer and does not discriminate on the basis of protected veteran status, disability, or other legally protected status.
• USA, CO, Boulder - 143,700.00 - 194,400.00 USD annually

Additional Information

Application deadline: Jun 28, 2026 Build the measurement systems that tell advertisers whether their ads actually work - processing 50 billion+ events daily using ML, causal inference, and petabyte-scale AWS infrastructure. Join a team where your code directly enables billions in optimized ad spend across all Amazon Ads products. We combine rigorous scientific experiments with deterministic and modeled measurement techniques to produce estimates that are fast, precise, and actionable. Using AWS big data and machine learning technologies (EMR, DynamoDB, Spark, Scala), we operate petabyte-scale clusters and continuously innovate on event-driven architectures to stay ahead of rapidly growing scale. We also leverage generative AI tools to accelerate our development, testing, and deployment cycles. Key job responsibilities - Design, build, and operate large-scale distributed systems that process 50B+ daily events for causal ad measurement - Develop and optimize data pipelines on petabyte-scale clusters using Spark, Scala, and AWS big data services (EMR, DynamoDB) - Implement and productionize machine learning models and causal inference methodologies - Innovate on event-driven architectures to handle rapidly growing data volumes - Collaborate with scientists and engineers to translate causal measurement research into production-grade systems - Leverage generative AI tools to accelerate development, testing, and deployment cycles - Own end-to-end system reliability including monitoring, alarming, and operational excellence A day in the life You'll work across the full stack of a measurement platform - from designing the data ingestion layer that handles billions of events, to building the ML infrastructure that powers causal estimates, to deploying production services that deliver real-time insights to advertisers. You'll partner closely with applied scientists to translate experimental designs into scalable systems, and you'll use GenAI tools to ship faster.

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