Responsibilities

• Design and implement deep learning models to match the right customers with the right ads across different verticals, geographies, and ads 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 models’ architecture.
• Work side by side with our engineers to deliver code changes impacting our 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 judgement.
• Be immersed in Amazon's advertisers and their objectives, and think 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.

Requirements

• 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 in building machine learning models for business application
• Experience in state-of-the-art deep learning models architecture design and deep learning training and optimization and model pruning

Preferred

• Experience in retrieval and ranking systems as applied to advertising or recommender systems