Applied Scientist, Sponsored Products Off-Search Auction

About the role

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.

This role will be pivotal in redesigning how ads contribute to a personalized, relevant, and inspirational shopping experience, with the customer value proposition at the forefront. As an Applied Scientist on the Sponsored Products and Brands Off-Search team, you will contribute to the development in Generative AI (GenAI) and Large Language Models (LLMs) to revolutionize our advertising flow, backend optimization, and frontend shopping experiences. This is a rare opportunity to redefine how ads are retrieved, allocated, and/or experienced—elevating them into personalized, context-aware, and inspiring components of the customer journey.

You will have the opportunity to fundamentally transform areas such as ad retrieval, ad allocation, whole-page relevance, and differentiated recommendations through the lens of GenAI. By building novel generative models grounded in both Amazon’s rich data and the world’s collective knowledge, your work will shape how customers engage with ads, discover products, and make purchasing decisions.

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 the 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.

About the team

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.

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. 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.

Requirements

• PhD, or Master's degree and 4+ years of CS, CE, ML or related field experience.
• 3+ years of building 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.

Preferred Qualifications

• 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.

Pay

• USA, CA, Palo Alto: $171,600.00 - $222,200.00 USD annually
• USA, NY, New York: $172,400.00 - $223,400.00 USD annually
• USA, WA, Seattle: $142,800.00 - $193,200.00 USD annually

Your Amazon package will include sign-on payments and restricted stock units (RSUs). Final compensation will be determined based on factors including experience, qualifications, and location.

Benefits

• Health insurance (medical, dental, vision, prescription, Basic Life & AD&D insurance and option for Supplemental life plans).
• Employee Assistance Program (EAP) and Mental Health Support.
• Medical Advice Line.
• Flexible Spending Accounts.
• Adoption and Surrogacy Reimbursement coverage.
• 401(k) matching.
• Paid time off and parental leave.

Learn more about our benefits at amazon.jobs/en/benefits.