The Community Feedback organization owns the experiences and systems that enable shoppers to provide and review trusted customer-generated content across the shopping journey. We bring together trusted, authentic inputs from the community and surface them with the help of AI so that customers can make effortless, high-confidence, purchase decisions. Features such as Customer Reviews, Content Moderation, and Customer Questions & Answers (Q&A), build a rewarding and engaging experience for creators to share their feedback, providing shoppers with trusted insights based on this feedback to inform their shopping decisions. We offer billions of star ratings and reviews with text, together with hundreds of millions of reviews and Q&A with media. Our vision is to make Amazon the internet’s most trustworthy, helpful, and delightful guide for customers on any shopping mission. Community Feedback materially impacts every retail marketplace, category and selling partner. Our features are a highly visible product, serving hundreds of millions of customers worldwide. Our team was the first to launch a customer-facing experience on Amazon that uses generative AI. Customer Reviews has received an overwhelming press coverage and S-Team visibility due to the launch of Review Highlights” feature - an AI-generated summary of text-based customer reviews. Since then, all customer-generated content has been used to power multiple high-profile experiences across the store such as Amazon’s Shopping AI Assistant (Rufus). The Principal Applied Scientist will be a thought leader and innovator to power this momentum and unlock further future value for customers. This role owns strategic projects in new and ambiguous areas leveraging advance machine learning techniques to create new scalable products. The customer problems to solve for can vary from how to rank and search content across the store, detect and mitigate abuse vectors such as fake reviews, to aggregate and summarize insights to help customers discover, compare, and purchase products at Amazon. This role requires experience and domain knowledge in NLP and ML, together with effective communication and collaboration skills to influence across multiple partnership teams including Search, Personalization, Rufus (Amazon’s Shopping AI Assistant) and Alexa. This position can be located in Barcelona, Madrid, or Berlin. Key job responsibilities As a Principal Applied Scientist, you are a trusted part of the technical leadership. You bring business and industry context to science and technology decisions. You set the standard for scientific excellence and make decisions that affect the way we build and integrate algorithms. You solicit differing views across the organization and are willing to change your mind as you learn more. You are a hands-on scientific leader you are tackling intrinsically hard problems, whose solutions are exemplary in terms of algorithm design, clarity, model structure, efficiency, and extensibility. You will be responsible for defining key research directions, adopting or inventing new machine learning techniques, conducting rigorous experiments, publishing results, and ensuring that research is translated into practice. You will develop long-term strategies, persuade teams to adopt those strategies, propose goals and deliver on them. You will also participate in organizational planning, hiring, mentorship and leadership development. You will be technically fearless and with a passion for building scalable science and engineering solutions. You will serve as a key scientific resource in full-cycle development (conception, design, implementation, testing to documentation, delivery, and maintenance). About the team The Community Shopping team is part of the Shopping Discovery & Evaluation team, and our vision is to make Amazon the internet’s most trustworthy, helpful, and delightful guide for customers on any shopping mission. From the moment customers visit our store, we help them find what they are looking for and delight in our vast offering of products and services (Navigation Experience). We create immersive, visual, and personalized shopping experiences that inspire customers to kickstart their next shopping journey (Inspire, Amazon Native Player). We bring together trusted, authentic inputs from the community, and surface those inputs with the help of generative AI, to help customers confidently inform their next purchase (Community Feedback).
