SoftwareDevelopmentEngineer

Amazon Advertising is one of Amazon's fastest growing and most profitable businesses. As a core product offering within our advertising portfolio, Sponsored Products (SP) helps merchants, retail vendors, and brand owners succeed via native advertising, which grows incremental sales of their products sold through Amazon. The SP team's primary goals are to help shoppers discover new products they love, be the most efficient way for advertisers to meet their business objectives, and build a sustainable business that continuously innovates on behalf of customers. Our products and solutions are strategically important to enable our Retail and Marketplace businesses to drive long-term growth. The Search Ranking and Interleaving (R&I) team within the Marketplace Intelligence org in SP is responsible for determining which ads to show in Amazon search, where to place them, how many ads to place, and to which customers. This helps shoppers discover new products while helping advertisers put their products in front of the right customers, aligning shoppers’, advertisers’, and Amazon’s interests. To do this, we apply a broad range of machine learning, causal inference, reinforcement learning based optimization techniques and LLMs to continuously explore, learn, and optimize the ranking and allocation of ads on the search page. We are an interdisciplinary team with a focus on customer obsession and inventing and simplifying. Our primary focus is on improving the SP experience in search by gaining a deep understanding of shopper pain points and developing new innovative solutions to address them. You will be on the Interleaving team. Our mission is to personalize and contextualize SP ad allocation on the search page. We do this by modeling shopper responses to the number, placement, and quality of ads. We are a data- and hypothesis-driven organization that uses online experimentation, simulation, causal modeling, and online feedback to place ads where they’re useful to shoppers a