Amazon
Overview
Join to apply for the
Applied Scientist, Sponsored Products
role at
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. 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.
The Off-Search team within Sponsored Products and Brands (SPB) is focused on building delightful ad experiences across surfaces beyond Search on Amazon, to drive monetization and deliver personalized, context-aware advertising that adapts to shopper preferences.
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.
What You’ll Do Day-to-Day
As an Applied Scientist on the Sponsored Products and Brands Off-Search team, you will contribute to the development of Generative AI (GenAI) and Large Language Models (LLMs) to revolutionize our advertising flow, backend optimization, and frontend shopping experiences. You will work on redefining how ads are retrieved, allocated, and experienced to become personalized and contextually aware components of the customer journey. You will help shape areas such as ad retrieval, ad allocation, whole-page relevance, and differentiated recommendations through GenAI, using Amazon’s data and world knowledge to influence customer engagement and purchasing decisions.
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 applications 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 RLHF Experience with online experimentation, A/B testing frameworks, and metrics design for advertising or e-commerce 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
Company & EEO
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. If the country/region you’re applying in isn’t listed, please contact your Recruiting Partner.
Compensation
Our compensation reflects the cost of labor across several US geographic markets. The base pay for this position ranges from $136,000/year in our lowest geographic market up to $223,400/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.
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Join to apply for the
Applied Scientist, Sponsored Products
role at
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. 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.
The Off-Search team within Sponsored Products and Brands (SPB) is focused on building delightful ad experiences across surfaces beyond Search on Amazon, to drive monetization and deliver personalized, context-aware advertising that adapts to shopper preferences.
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.
What You’ll Do Day-to-Day
As an Applied Scientist on the Sponsored Products and Brands Off-Search team, you will contribute to the development of Generative AI (GenAI) and Large Language Models (LLMs) to revolutionize our advertising flow, backend optimization, and frontend shopping experiences. You will work on redefining how ads are retrieved, allocated, and experienced to become personalized and contextually aware components of the customer journey. You will help shape areas such as ad retrieval, ad allocation, whole-page relevance, and differentiated recommendations through GenAI, using Amazon’s data and world knowledge to influence customer engagement and purchasing decisions.
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 applications 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 RLHF Experience with online experimentation, A/B testing frameworks, and metrics design for advertising or e-commerce 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
Company & EEO
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. If the country/region you’re applying in isn’t listed, please contact your Recruiting Partner.
Compensation
Our compensation reflects the cost of labor across several US geographic markets. The base pay for this position ranges from $136,000/year in our lowest geographic market up to $223,400/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.
#J-18808-Ljbffr