Description
Orchestrating the selection of one ad out of tens of millions of ads, honoring advertiser targeting intent for hundreds of thousands of advertisers while ensuring a great shopper experience for billions of shoppers millions of times per second on a latency of tens of milliseconds is not a trivial task. The Demand Retrieval team within the Amazon DSP organization develops and operates machine learning models that match bid opportunities to ads based on performance, campaign delivery, and targeting objectives specified by advertisers.
Job Responsibilities
- Design and implement deep learning models to match the right customers with the right ads across different verticals, geographies, and ad formats.
- Investigate new ML techniques such as multi‑task learning to ensure that models can operate for a variety of advertisers in multiple industries and with different volumes of conversion events.
- Improve the performance, generalisation, and scalability of models by introducing new features and enhancing model architectures.
- Work side by side with engineers to deliver code changes impacting the ads stack, working with very large datasets and high‑throughput production systems.
- Rapidly prototype and test many possible hypotheses/implementation alternatives in a high‑ambiguity environment, making use of both quantitative analysis and business judgment.
- Be immersed in Amazon’s advertisers and their objectives, thinking long‑term about how to turn those objectives into products and technical capabilities.
- Understand the latest literature on machine learning for recommender and advertising systems, contributing to guiding strategic investment for the organization.
Team Overview
The Demand Retrieval team is responsible for designing, implementing, deploying, and operating machine learning models that match bid opportunities to ads demand based on performance, campaign delivery, and targeting objectives specified by advertisers. Success is measured by offline experimentation and online metrics that reflect the impact of our matching models on campaign KPIs such as cost per action, return on ad investment, budgets delivered, and targeting precision.
Basic Qualifications
- PhD, or a Master’s degree and experience in CS, CE, ML, or related field research.
- Experience programming in Java, C++, Python, or related language.
- Experience building machine learning models for business application.
- Experience in state‑of‑the‑art deep learning model architecture design, training, optimization, and model pruning.
Preferred Qualifications
- Experience in retrieval and ranking systems as applied to advertising or recommender systems.
Equal Opportunity Statement
Amazon is an equal‑opportunity employer. We value your passion to discover, invent, simplify, and build. We protect your privacy and the security of your data. Please consult our Privacy Notice to learn how we collect, use, and transfer the personal data of our candidates. Amazon is an equal opportunity employer and does not discriminate on the basis of protected veteran status, disability, or other legally protected status. If you have a disability and need a workplace accommodation or adjustment during the application and hiring process, please visit for more information.
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