Amazon is the 4th most popular site in the US (source:http://www.alexa.com/topsites/countries/US). Our product search engine,one of the most heavily used services in the world, indexes billions of products and serves hundreds of millions of customers world-wide. We are working on a new AI-first initiative to re-architect and reinvent our search engine into a shopping engine that assists customers with their shopping missions. We're looking at asking how we can make big, step improvements by applying advanced Machine Learning (ML) and Deep Learning techniques, including Deep Reinforcement Learning. This is a rare opportunity to develop cutting edge ML solutions and apply them to a search problem of this magnitude. Some exciting questions that we expect to answer over the next few years include:
* Can we deeply understand customer intent and personalize their search experience even when they type broad queries such as "dress" or"espresso machine" by using deep reinforcement learning to infer their preferences from their engagement with displayed content? * Can we reduce the cost of serving customer queries on Amazon by orders of magnitude using ML to predict n-grams and tuples that many queries decompose into, apply expensive ranking functions offline to identify the most relevant products that match these terms, and index these for efficient online retrieval? We expect this to lead to exciting research at the intersection of systems and ML. * Can we deeply understand the catalog to surface products that offer the most value to a customer? The challenge here is that the definition of value is subjective and personal, and therefore requires a deeper understanding of the customers intent as well as preferences. * Can we use deep learning to transfer behavioral signals from frequently purchased products in the head to products in the tail where behavioral signals are sparse? The challenge here is the scale, and the fact that the head and torso contain only a small fraction of products while the tail contains an overwhelmingly large fraction of the products in the catalog.
This is a unique opportunity to get in on the ground floor and shape and build the next-generation of Amazon Search. We are looking for candidates who will bring deep technical and engineering skills, and are comfortable with ambiguity and working in a team with a startup culture within a larger organization.
Amazon is a company operating a marketplace for consumers, sellers, and content creators.