Our goal is to be Earth's most customer-centric company, where customers can find and discover anything they might want to buy online. We have been delighting our customers with recommendations by constantly improving on the quality and performance of these recommendations. Our mission is to create intuitive tools to help other developers deliver recommendations features more efficiently and to better measure their performance. Are you passionate about working on disruptive ideas? Are you obsessed with finding and building innovative user experiences? Are you enthusiastic about solving big data problems? This is a unique opportunity that combines the ability to build exciting, new user experiences for internal customers, with the opportunity to work with big data, automation, and other advanced technologies.
About you:
Key job responsibilities:
About the team:
Amazon's Personalization organization is a high-performing group that leverages Amazon's expertise in machine learning, big data, and distributed systems to deliver the best shopping experiences for our customers. We run hundreds of experiments each year and our work has revolutionized e-commerce with features such as "Customers Who Bought Also Bought" and "Recommended for You". This team strives to help the organization deliver on these features with high quality and efficiency. We also provide the organization with tools to understand their features' performances. We care deeply about our customers, as well as the well-being and growth of our team members. Amazon's internal surveys regularly recognize us as one of the best engineering organizations to work for in the company, with visible high-impact work, low operational load, respectful work-life balance, and continual opportunity to learn and grow. This is a track record we are proud of and will continue to uphold. We are looking for creative and innovative leaders with a similar penchant for deeply-technical problem solving and the ability to lead, mentor, and deliver while upholding Amazon's leadership principles.