Senior Applied Scientist, Sponsored Products and Brands Off-Search

Senior Applied Scientist, Sponsored Products and Brands Off-Search

Job ID: 3102449 | Amazon.com Services LLC

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.

Key Job 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.

A Day in the Life

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 optimisation, and frontend shopping experiences. This is a rare opportunity to redefine how ads are retrieved, allocated, and/or experienced—elevating them into personalised, 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.

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 monetisation. Our vision is to deliver highly personalised, 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.

Basic Qualifications

• PhD, or Master’s degree and 8+ 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 modelling, and/or optimisation
• 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 customisation for downstream tasks
• Hands‑on experience in ads ranking, retrieval, recommendation systems, search, or personalization at web scale
• Deep understanding of multi‑modal modelling, 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

Amazon is an equal opportunity employer and does not discriminate on the basis of protected veteran status, disability, or other legally protected status.

Our compensation reflects the cost of labour across several US geographic markets. The base pay for this position ranges from $150,400/year in our lowest geographic market up to $260,000/year in our highest geographic market. Pay is based on a number of factors including market location and may vary depending on job‑related knowledge, skills, and experience. Amazon is a total compensation company. Dependent on the position offered, equity, sign‑on payments, and other forms of compensation may be provided as part of a total compensation package, in addition to a full range of medical, financial, and/or other benefits. For more information, please visit https://www.aboutamazon.com/workplace/employee-benefits. This position will remain posted until filled. Applicants should apply via our internal or external career site.