Amazon Advertising is looking for highly skilled and experienced software engineers to drive the development of next-generation solutions that enable advertisers to reach customers across our owned and operated sites, as well as other high-quality publisher sites on the web, and on millions of desktops, mobile devices, and connected TV platforms. Our mission is to offer the world's most customer-centric advertising solutions, leveraging our unique datasets, AI/ML technologies, and AWS infrastructure.
Amazon's DemandTech Platform is the company's programmatic advertising product, supporting campaigns spanning Display, Video, and Audio across Amazon properties (e.g., Amazon.com, Prime Video, Freevee, Twitch, and Amazon Music) and tens of thousands of third-party websites and applications. We are seeking candidates who wish to join a team focused on building large-scale systems that integrate data from multiple sources to provide unique and impactful advertising products.
Amazon DemandTech is seeking an experienced Senior Software Engineer to join the Maestro ML platform - Training team. In this role, you will be responsible for building and scaling AI/ML infrastructure for real-time bidding. The target systems require high availability and will handle state of the art model training leveraging vast amount of advertising data. Working closely with other engineers and scientists, you will have the opportunity to contribute to the long-term architectural vision. You will develop and maintain scalable software solutions supporting data pipelines, analytical tools, and machine learning infrastructure. You will collaborate with data scientists, analysts, and product managers to deliver production-grade software. Ideal candidates have strong technical skills, experience in building reliable software, and can effectively operate in a dynamic environment.

Key job responsibilities
- Design and develop scalable software systems and data infrastructure to address business challenges.
- Implement efficient and robust services to support ML model training, and deployment.
- Collaborate with scientists and analysts to operationalize machine learning models and integrate them into production systems.
- Conduct thorough code reviews, ensuring reliability, efficiency, and maintainability of solutions.
- Develop and run regular A/B testing infrastructure, ensuring accuracy and scalability in experiments.
- Provide technical guidance and mentorship to other software development engineers on the team.