Within Amazon Search, the Relevance team has a mission to help customers efficiently find anything they are looking for. This charter requires us to build innovative ranking solutions that operate at Amazon's scale, across diverse product categories, and focus on our customers' long-term satisfaction. We dive deep to figure out idiosyncrasies of how customers shop , make purchase decisions for their business, browse the catalog, or choose things to buy, then we turn these learnings into innovative machine learned ranking solutions to improve customer satisfaction and business metrics.
In this role you will leverage your strong engineering background to help build the next generation of our ranking model development and assessment framework, harnessing and explaining rich data at Amazon scale, and providing automated insights to ensure the quality and operational stability of machine learned rankers that impact millions of customers every day. This role requires a pragmatic problem solver comfortable with ambiguity, with deep expertise in data processing at scale. The ideal candidate will have deep experience in data processing at scale in customer-facing applications. Additionally, we are seeking candidates with strong rigor in engineering, deep curiosity and interest for applied sciences, creativity, and great judgment.
As a member of our Search team, you will work alongside internationally recognized experts in science and engineering to develop novel algorithms and modeling techniques to advance the state-of-the-art in search and natural language processing. You will be expected to collaborate with the Core AI group in Barcelona and other groups at Amazon including Search.