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Applied Scientist, Sponsored Products Off-Search Homepage Team
Amazon
H1B ✓On-sitesenior levelPosted April 24, 2026
About the Role
Develop and deploy advanced AI models including GenAI and LLMs to optimize ad retrieval, auctions, and personalized shopping experiences. Collaborate with cross-functional teams to scale production-ready science solutions and mentor junior staff.
Requirements
Requires a PhD or Master's degree in a technical field with at least 4 years of relevant experience. Candidates must have a strong background in machine learning, model development, and programming in languages like Python, Java, or C++.
Full Job Description
The Sponsored Products and Brands (SPB) team at Amazon Ads is re-imagining advertising through generative AI, transforming how millions of customers discover products and engage with brands across Amazon.com and beyond. We bridge human creativity with artificial intelligence across the full advertising lifecycle—from ad creation and optimization to performance analysis and customer insights.
Within SPB, the Off-Search team builds ad experiences across surfaces beyond Search—product detail pages, the homepage, and store-in-store pages. Our team is specifically focused on ad and experience expansion on Homepage: growing the number of ad placements, introducing new widget formats, and delivering richer, more personalized ad experiences that integrate naturally with the shopping journey. We partner with Amazon Stores to ensure ads complement organic recommendations—new arrivals, deals, basket-building content, and fast-delivery options—while adapting to shopper preferences, seasonal moments, and diverse page layouts. We operate full stack, from backend retrieval and auction systems to the shopper-facing experience layer.
If you're energized by solving complex challenges at the intersection of ads, personalization, and customer experience, join us in shaping the future of advertising on Amazon's most visited surface.
Key job responsibilities
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. Key responsibilities include, but are not limited to:
- 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.
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 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.
About the team
The Off-Search team within Sponsored Products and Brands (SPB) is focused on building delightful ad experiences across surfaces beyond Search on Amazon—such as product detail pages, the homepage, and store-in-store pages—to drive monetization. Our Homepage team is at the center of this mission, leveraging large language models (LLMs) to build a new generation of personalized ad experiences that understand shopper intent, adapt to individual preferences, and deliver contextually relevant creatives in real time. Beyond Homepage, we are designing these experiences as reusable building blocks that can scale across other pages on Amazon—detail pages, browse, store-in-store, and emerging surfaces—so that innovation on one page accelerates growth everywhere. We operate full stack, from backend ads-retail edge services, ads retrieval, and ad auctions to shopper-facing experiences, working in close partnership with Amazon Stores to integrate advertising seamlessly alongside organic content like new arrivals, basket-building recommendations, and fast-delivery options.
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!
Basic Qualifications: - 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
- 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
- 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.
Amazon is an equal opportunity employer and does not discriminate on the basis of protected veteran status, disability, or other legally protected status.
Los Angeles County applicants: Job duties for this position include: work safely and cooperatively with other employees, supervisors, and staff; adhere to standards of excellence despite stressful conditions; communicate effectively and respectfully with employees, supervisors, and staff to ensure exceptional customer service; and follow all federal, state, and local laws and Company policies. Criminal history may have a direct, adverse, and negative relationship with some of the material job duties of this position. These include the duties and responsibilities listed above, as well as the abilities to adhere to company policies, exercise sound judgment, effectively manage stress and work safely and respectfully with others, exhibit trustworthiness and professionalism, and safeguard business operations and the Company’s reputation. Pursuant to the Los Angeles County Fair Chance Ordinance, we will consider for employment qualified applicants with arrest and conviction records.
Our inclusive culture empowers Amazonians to deliver the best results for our customers. If you have a disability and need a workplace accommodation or adjustment during the application and hiring process, including support for the interview or onboarding process, please visit https://amazon.jobs/content/en/how-we-hire/accommodations for more information. If the country/region you’re applying in isn’t listed, please contact your Recruiting Partner.
USA, CA, Palo Alto - 171,600.00 - 222,200.00 USD annually
Within SPB, the Off-Search team builds ad experiences across surfaces beyond Search—product detail pages, the homepage, and store-in-store pages. Our team is specifically focused on ad and experience expansion on Homepage: growing the number of ad placements, introducing new widget formats, and delivering richer, more personalized ad experiences that integrate naturally with the shopping journey. We partner with Amazon Stores to ensure ads complement organic recommendations—new arrivals, deals, basket-building content, and fast-delivery options—while adapting to shopper preferences, seasonal moments, and diverse page layouts. We operate full stack, from backend retrieval and auction systems to the shopper-facing experience layer.
If you're energized by solving complex challenges at the intersection of ads, personalization, and customer experience, join us in shaping the future of advertising on Amazon's most visited surface.
Key job responsibilities
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. Key responsibilities include, but are not limited to:
- 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.
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 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.
About the team
The Off-Search team within Sponsored Products and Brands (SPB) is focused on building delightful ad experiences across surfaces beyond Search on Amazon—such as product detail pages, the homepage, and store-in-store pages—to drive monetization. Our Homepage team is at the center of this mission, leveraging large language models (LLMs) to build a new generation of personalized ad experiences that understand shopper intent, adapt to individual preferences, and deliver contextually relevant creatives in real time. Beyond Homepage, we are designing these experiences as reusable building blocks that can scale across other pages on Amazon—detail pages, browse, store-in-store, and emerging surfaces—so that innovation on one page accelerates growth everywhere. We operate full stack, from backend ads-retail edge services, ads retrieval, and ad auctions to shopper-facing experiences, working in close partnership with Amazon Stores to integrate advertising seamlessly alongside organic content like new arrivals, basket-building recommendations, and fast-delivery options.
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!
Basic Qualifications: - 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
- 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
- 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.
Amazon is an equal opportunity employer and does not discriminate on the basis of protected veteran status, disability, or other legally protected status.
Los Angeles County applicants: Job duties for this position include: work safely and cooperatively with other employees, supervisors, and staff; adhere to standards of excellence despite stressful conditions; communicate effectively and respectfully with employees, supervisors, and staff to ensure exceptional customer service; and follow all federal, state, and local laws and Company policies. Criminal history may have a direct, adverse, and negative relationship with some of the material job duties of this position. These include the duties and responsibilities listed above, as well as the abilities to adhere to company policies, exercise sound judgment, effectively manage stress and work safely and respectfully with others, exhibit trustworthiness and professionalism, and safeguard business operations and the Company’s reputation. Pursuant to the Los Angeles County Fair Chance Ordinance, we will consider for employment qualified applicants with arrest and conviction records.
Our inclusive culture empowers Amazonians to deliver the best results for our customers. If you have a disability and need a workplace accommodation or adjustment during the application and hiring process, including support for the interview or onboarding process, please visit https://amazon.jobs/content/en/how-we-hire/accommodations for more information. If the country/region you’re applying in isn’t listed, please contact your Recruiting Partner.
The base salary range for this position is listed below. 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. Amazon also offers comprehensive benefits including 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, and parental leave. Learn more about our benefits at https://amazon.jobs/en/benefits.
USA, CA, Palo Alto - 171,600.00 - 222,200.00 USD annually