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

Amazon.com Inc

Boulder, CO

JOB DETAILS
SKILLS
Amazon Web Services (AWS), Apache Spark, Artificial Intelligence (AI), Autoscaling, Big Data, Data Management, Data Science, Distributed Computing, Electronic Medical Records, Experiment Design, Large-Scale Systems, Machine Learning, Production Machining, Production Systems, Scala Programming Language, Software Development, Software Engineering, Systems Reliability, Systems Scalability, Test Plan/Schedule
LOCATION
Boulder, CO
POSTED
17 days ago

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.

About the team

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.

About the Company

A

Amazon.com Inc

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
COMPANY SIZE
10,000 employees or more
INDUSTRY
Retail
FOUNDED
1994
WEBSITE
http://Amazon.com/militaryroles