Amazon Advertising is one of Amazon's fastest growing and most profitable businesses, responsible for defining and delivering a collection of advertising products that drive discovery and sales. 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 organization'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. We deliver billions of ad impressions and millions of clicks and break fresh ground in product and technical innovations every day!
As the detail page, homepage, and other Stores touchpoints continue to evolve, the Sponsored Products (SP) Off-Search organization is focused on building delightful ad experiences across these surfaces to drive monetization. Our vision is to deliver highly personalized, context-aware advertising that adapts to individual shopper preferences (multi-persona), scales across diverse page types such as the homepage, detail page, and store-in-store surfaces (multi-surface), stays relevant to seasonal and event-driven moments (multi-moment), and integrates seamlessly with organic recommendations such as new arrivals, basket-building content, and fast-delivery options (multi-intent). To execute this vision, we work closely with Stores stakeholders, spearhead the expansion of SP across Amazon-owned and operated pages, develop advanced ML and GenAI/LLM models, engineering systems, Tier-1 services, to optimize end-to-end ads flow from sourcing, auction to frontend customer experiences.
We are looking for a passionate Senior Applied Scientist who has technical expertise in information retrieval, Natural Language Processing (NLP), Large Language Models (LLM), Online Advertising, and/or randomized experiments. In addition to having hands-on experience in building ML-based solutions, an ideal candidate should be able to create and articulate a customer-centric science vision, show willingness to continuously learn about new scientific approaches, and enjoy operating in startup-like environment.
Key job responsibilities
• Lead business, science and engineering strategy and roadmap for Sponsored Products Off-Search Sourcing and Relevance.
• Drive alignment across teams for science, engineering, and product strategy to achieve business goals.
• Lead/guide scientists and engineers across teams to develop, test, launch and improve of science models designed to optimize the shopper experience and deliver long term value for Amazon and advertisers
• Develop state of the art experimental approaches and ML models.
