Description Amazon is investing heavily in building a world-class advertising business to define and deliver a collection of ad products that drive long-term customer value. Our team, Sponsored Brands (SB), owns a mid-funnel ad product dedicated for brand owners. We empower brands of all shapes and sizes to attract shoppers in the research and consideration phases of their shopping journey, through visually stunning, inspiring and relevant sponsored shopping experiences. In doing so, we deliver billions of ad impressions and millions of clicks daily, but are only just getting started. The SB Sourcing and Relevance team consists entrepreneurial machine learning scientists and engineers who are responsible for developing core machine learning models and model development pipelines. Through precise estimation of shoppers’ interaction with brand ads and their long-term value, we aim to drive optimal ads retrieval and ranking, and help to deliver a relevant, engaging and delightful ads experience to Amazon shoppers. All of these, powered by state-of-the-art machine learning models, take place in milliseconds. We are looking for an experienced Applied Scientist who is passionate for building machine learning solutions, and communicating science insights, and executing strategic projects. You will work with business partners to design, implement and launch machine learning solutions. You will innovate machine learning models and LLM to connect shoppers with brand ads via shopper intent understanding as well as brand ads interpreting. This is a unique opportunity to stand at the intersection of e-commerce, advertising and state-of-the-art machine learning techniques. As an Senior Applied Scientist on this team you will: - Research and prototype LLM power ad retrieval - Work closely with software engineers on detailed requirements, technical designs and implementation of end-to-end solutions in production. - Build machine learning models and utilize data analysis to deliver scalable solutions to business problems. - Perform hands-on analysis and modeling with very large data sets to develop insights that increase traffic monetization and merchandise sales without compromising shopper experience. - Design and run A/B experiments that affect hundreds of millions of customers, evaluate the impact of your optimizations and communicate your results to various business stakeholders. - Establish scalable, efficient, automated processes for large-scale data analysis, machine-learning model development, model validation and serving. - Write code to bring models into production. Why you love this opportunity Amazon is investing heavily in building a world-class advertising business. This team is responsible for defining and delivering a collection of advertising products that drive discovery and sales. Our solutions generate billions in revenue and drive long-term growth for Amazon’s Retail and Marketplace businesses. We deliver billions of ad impressions, millions of clicks daily, and break fresh ground to create world-class products. We are highly motivated, collaborative, and fun-loving team with an entrepreneurial spirit - with a broad mandate to experiment and innovate. Impact and Career Growth You will invent new experiences and influence customer-facing shopping experiences to help suppliers grow their retail business and the auction dynamics that leverage native advertising; this is your opportunity to work within the fastest-growing businesses across all of Amazon! Define a long-term science vision for our advertising business, driven fundamentally from our customers' needs, translating that direction into specific plans for research and applied scientists, as well as engineering and product teams. This role combines science leadership, organizational ability, technical strength, product focus, and business understanding. Basic Qualifications - 3+ years of building machine learning models for business application experience - PhD, or Master's degree and 6+ years of applied research experience - Experience programming in Java, C++, Python or related language - Experience with neural deep learning methods and machine learning Preferred Qualifications - Experience with modeling tools such as R, scikit-learn, Spark MLLib, MxNet, Tensorflow, numpy, scipy etc. - Experience with large scale distributed systems such as Hadoop, Spark etc. Amazon is an equal opportunity employer and does not discriminate on the basis of protected veteran status, disability, or other legally protected status. Our inclusive culture empowers Amazonians to deliver the best results for our customers. If you have a disability and need a workplace accommodation or adjustment during the application and hiring process, including support for the interview or onboarding process, please visit https://amazon.jobs/content/en/how-we-hire/accommodations for more information. If the country/region you’re applying in isn’t listed, please contact your Recruiting Partner. Our compensation reflects the cost of labor across several US geographic markets. The base pay for this position ranges from $150,400/year in our lowest geographic market up to $260,000/year in our highest geographic market. Pay is based on a number of factors including market location and may vary depending on job-related knowledge, skills, and experience. Amazon is a total compensation company. Dependent on the position offered, equity, sign-on payments, and other forms of compensation may be provided as part of a total compensation package, in addition to a full range of medical, financial, and/or other benefits. For more information, please visit https://www.aboutamazon.com/workplace/employee-benefits . This position will remain posted until filled. Applicants should apply via our internal or external career site.