Senior Applied Scientist, Off-Search, Sponsored Products and Brands

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.

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!

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, contextually 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. If you are passionate about applying frontier AI to

real-world problems with massive scale and impact, this is your opportunity to

define the next chapter of advertising science.

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.

Responsibilities

• Design and develop solutions using GenAI, deep learning, multi-objective

optimization and/or reinforcement learning to transform ad retrieval, auctions,

whole-page relevance, and shopping experiences.

• Partner with scientists, engineers, and product managers to build scalable,

production-ready science solutions.

• Apply industry advances in GenAI, Large Language Models (LLMs), and related

fields to create innovative prototypes and concepts.

• Improve the team's scientific and technical capabilities by implementing

algorithms, methodologies, and infrastructure that enable rapid experimentation

and scaling.

• Mentor junior scientists and engineers to build a high-performing,

collaborative team.

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
• Experience with Machine Learning and Large Language Model fundamentals,

including architecture, training/inference lifecycles, and optimization of model

execution, or experience in machine learning, data mining, information

retrieval, statistics or natural language processing

Nice-to-haves

• Demonstrated expertise in Generative AI technologies, including foundation

models, LLMs, and model customization for specific business applications

• Hands-on experience building ads ranking, retrieval, recommendation, or

personalization systems that operate at web scale

• Technical proficiency in advanced AI approaches such as multi-modal modeling,

few-shot learning, retrieval-augmented generation (RAG), or reinforcement

learning from human feedback (RLHF)

• Track record of designing and implementing online experimentation frameworks,

including A/B testing methodologies and performance metrics for advertising or

e-commerce

• Proven ability to translate complex technical concepts into clear explanations

for diverse audiences, from engineers to executives

• Deep knowledge of computational advertising fundamentals, including auction

mechanisms, advertising economics, and advertiser success metrics

Benefits

• health insurance (medical, dental, vision, prescription, Basic Life &

AD&D insurance and option for Supplemental life plans, EAP, Mental Health

Support, Medical Advice Line, Flexible Spending Accounts, Adoption and Surrogacy

Reimbursement coverage)

• 401(k) matching
• paid time off
• parental leave