Sr. Applied Scientist, Sponsored Product Off-Search

Amazon • Seattle, WA

61d

About The Position

The Sponsored Products and Brands (SPB) team at Amazon Ads is re-imagining the advertising landscape through state-of-the-art generative AI technologies, revolutionizing how millions of customers discover products and engage with brands across Amazon.com and beyond. We are at the forefront of re-inventing advertising experiences, bridging human creativity with artificial intelligence to transform every aspect of the advertising lifecycle from ad creation and optimization to performance analysis and customer insights. We are a passionate group of innovators dedicated to developing responsible and intelligent AI technologies that balance the needs of advertisers, enhance the shopping experience, and strengthen the marketplace. If you're energized by solving complex challenges and pushing the boundaries of what's possible with AI, join us in shaping the future of advertising. The Off-Search team within Sponsored Products and Brands (SPB) is focused on building delightful ad experiences across various surfaces beyond Search on Amazon—such as product detail pages, the homepage, and store-in-store pages—to drive monetization. Our vision is to deliver highly personalized, context-aware advertising that adapts to individual shopper preferences, scales across diverse page types, remains relevant to seasonal and event-driven moments, and integrates seamlessly with organic recommendations such as new arrivals, basket-building content, and fast-delivery options. To execute this vision, we work in close partnership with Amazon Stores stakeholders to lead the expansion and growth of advertising across Amazon-owned and -operated pages beyond Search. We operate full stack—from backend ads-retail edge services, ads retrieval, and ad auctions to shopper-facing experiences—all designed to deliver meaningful value. Curious about our advertising solutions? Discover more about Sponsored Products and Sponsored Brands to see how we’re helping businesses grow on Amazon.com and beyond!

Requirements

• PhD, or Master's degree and 6+ years of applied research experience
• 3+ years of building machine learning models for business application experience
• Experience programming in Java, C++, Python or related language
• Strong foundation in GenAI, large language models, machine learning, deep learning, probabilistic modeling, and/or optimization.
• Experience developing and deploying models in real-world production environments.

Nice To Haves

• Proven expertise in Generative AI, foundation models, LLMs, and/or fine-tuning and customization for downstream tasks.
• Hands-on experience in ads ranking, retrieval, recommendation systems, search, or personalization at web scale.
• Deep understanding of multi-modal modeling, few-shot learning, retrieval-augmented generation (RAG), or reinforcement learning from human feedback (RLHF).
• Experience with online experimentation, A/B testing frameworks, and metrics design for advertising or e-commerce.
• Demonstrated ability to communicate complex technical topics clearly to both technical and non-technical audiences.
• Experience in computational advertising, including familiarity with auction theory, ad economics, and advertiser performance metrics.

Responsibilities

• Contribute to the design and development of GenAI, deep learning, multi-objective optimization and/or reinforcement learning empowered solutions to transform ad retrieval, auctions, whole-page relevance, and/or bespoke shopping experiences.
• Collaborate cross-functionally with other scientists, engineers, and product managers to bring scalable, production-ready science solutions to life.
• Stay abreast of industry trends in GenAI, LLMs, and related disciplines, bringing fresh and innovative concepts, ideas, and prototypes to the organization.
• Contribute to the enhancement of team’s scientific and technical rigor by identifying and implementing best-in-class algorithms, methodologies, and infrastructure that enable rapid experimentation and scaling.
• Mentor and grow junior scientists and engineers, cultivating a high-performing, collaborative, and intellectually curious team.

What This Job Offers

• Job Type: Full-time
• Career Level: Mid Level
• Education Level: Ph.D. or professional degree