Amazon
The Sponsored Products and Brands (SPB) team at Amazon Ads is re-imagining the advertising landscape through the latest 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.
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.
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: 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. 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. Basic Qualifications
Required: 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
Preferred: 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. 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.
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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: 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. 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. Basic Qualifications
Required: 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
Preferred: 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. 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.
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