Are you interested in big data, machine learning, LLM, and product recommendations? If so, Amazon's Personalization team might be the right place for you. About our organization: We are part of Amazon’s Personalization organization, a high-performing group with a huge impact on hundreds of millions of customers, innovating at the intersection of customer experience, machine learning, and large-scale distributed systems. We run global experiments and our work has revolutionized e-commerce with features such as "Compare with similar items", "Keep shopping for ...", “Customers who bought this item also bought”, and, “Frequently bought together” among others. Amazon’s internal surveys regularly recognize us as one of the best organizations to work for in the company, with visible high-impact work, low operational load, respectful work-life balance, and continuous opportunity to learn and grow. About you: You are an Applied Scientist who loves big data and passionate about improving customer shopping experience by inventing and applying state-of-art technologies (e.g., LLM, Machine Learning, NLP, and Computer Vision) to build the next-generation product recommendation engine for Amazon. You have an entrepreneurial spirit, know how to deliver, are deeply technical and highly innovative. You work closely with software engineers to put algorithms into production. You also work in partnership with teams across Amazon to create enormous benefits for our customers. You will have an opportunity to make an enormous impact on the design, architecture, and implementation of products used every day by people you know. About the team Our mission is to delight every Amazon customer with a personalized shopping experience. We achieve our mission through investments in large-scale machine learning and distributed system solutions with the purpose of delivering the future of shopping on Amazon. Our solutions help customers explore product categories, discover high quality products that meet their needs, and provide most relevant information to help customers make confident shopping decisions. We are seeking an Applied Scientist to make step function improvements in creating a delightful shopping experience.
Stand Out From the Crowd
Upload your resume and get instant feedback on how well it matches this job.
Job Type
Full-time
Career Level
Mid Level
Education Level
Ph.D. or professional degree