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Senior Applied Scientist, Sponsored Products
Job Location:
Job Location:
Seattle, WA - USA
Monthly Salary:
Not provided by the employer
Monthly Salary:
Posted:
13 July 2026 (30+ days ago)
Posted:
Application Deadline:
10 October 2026
Application Deadline:
Vacancies:
1 Vacancy
Vacancies:
Job Summary
The Sponsored Products and Brands team at Amazon Ads is re-imagining the advertising landscape through cutting-edge generative AI technologies revolutionizing how millions of customers discover products and engage with brands across 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 youre energized by solving complex challenges and pushing the boundaries of whats possible with AI join us in shaping the future of advertising.
The Sponsored Products Search Sourcing Science (SPSSS) teams mission is to retrieve all relevant sponsored products in response to shopper queries serving billions of daily ad impressions and tens of millions of clicks helping shoppers discover useful and contextually relevant products while enabling advertisers to reach the right shoppers in the right context. To achieve this we build state-of-the-art capabilities spanning query shopper product and advertiser understanding as well as advanced retrieval targeting and ranking systems all powered by efficient large-scale data pipelines deep learning natural language processing (NLP) generative AI and multi-agent workflows. Its a high-impact technically exciting space where science directly translates into measurable outcomes for hundreds of millions of customers and millions of advertisers.
Key job responsibilities
As a Senior Applied Scientist on this team you will:
- Serve as the technical leader in Machine Learning and Generative AI driving efforts within this team and across other teams.
- Lead end-to-end ML projects with high ambiguity scale and complexityfrom problem definition to production.
- Build optimize and deploy ML models into production partnering with software engineers to productionize solutions.
- Establish scalable automated processes for data analysis model development validation and serving.
- Apply strong knowledge of LLMs (prompt engineering fine-tuning RAG evaluation) to build production-grade GenAI applications.
- Analyze large-scale data sets to develop insights that increase traffic monetization and merchandise sales without compromising the shopper experience.
- Design and run A/B experiments and perform statistical analysis to measure impact and guide decisions.
- Research and prototype innovative ML and GenAI approaches bringing state-of-the-art techniques into production.
- Recruit mentor and grow Applied Scientists on the team.
About the team
Amazon is investing heavily in building a world-class advertising business. This team defines and delivers a collection of advertising products that drive discovery and sales. Our solutions generate billions in revenue and drive long-term growth for Amazons Retail and Marketplace businesses. We deliver billions of ad impressions millions of clicks daily and break fresh ground to create world-class products. We are a highly motivated collaborative and fun-loving team with an entrepreneurial spirit - with a broad mandate to experiment and innovate.
The Sponsored Products Search Sourcing Science (SPSSS) teams mission is to retrieve all relevant sponsored products in response to shopper queries serving billions of daily ad impressions and tens of millions of clicks helping shoppers discover useful and contextually relevant products while enabling advertisers to reach the right shoppers in the right context. To achieve this we build state-of-the-art capabilities spanning query shopper product and advertiser understanding as well as advanced retrieval targeting and ranking systems all powered by efficient large-scale data pipelines deep learning natural language processing (NLP) generative AI and multi-agent workflows. Its a high-impact technically exciting space where science directly translates into measurable outcomes for hundreds of millions of customers and millions of advertisers.
- 3 years of building machine learning models for business application experience
- PhD or Masters degree and 6 years of applied research experience
- Experience programming in Java C Python or related language
- Experience with neural deep learning methods and machine learning
- Experience in building speech recognition machine translation and natural language processing systems (e.g. commercial speech products or government speech projects)
- Experience with large scale machine learning systems such as profiling and debugging and understanding of system performance and scalability
- Masters degree or above in engineering statistics computer science mathematics or a related quantitative field
- Experience in patents or publications at top-tier peer-reviewed conferences or journals
- 3 years of building large-scale machine-learning infrastructure for online recommendation ads ranking personalization or search experience
- Experience in machine learning data mining information retrieval statistics or natural language processing or experience leading engineering teams as a mentor or tech lead
- Experience creating and delivering written and oral communications for technical and non-technical audiences
- Experience in data science business analytics business intelligence or similar experience in big data environments
- Thinks strategically but stays on top of tactical execution.
- Exhibits excellent business judgment; balances business product and technology very well.
- Experience in computational advertising.
- Experience in Large Language Models (LLMs).
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 for more information. If the country/region youre applying in isnt listed please contact your Recruiting Partner.
The Sponsored Products Search Sourcing Science (SPSSS) teams mission is to retrieve all relevant sponsored products in response to shopper queries serving billions of daily ad impressions and tens of millions of clicks helping shoppers discover useful and contextually relevant products while enabling advertisers to reach the right shoppers in the right context. To achieve this we build state-of-the-art capabilities spanning query shopper product and advertiser understanding as well as advanced retrieval targeting and ranking systems all powered by efficient large-scale data pipelines deep learning natural language processing (NLP) generative AI and multi-agent workflows. Its a high-impact technically exciting space where science directly translates into measurable outcomes for hundreds of millions of customers and millions of advertisers.
Key job responsibilities
As a Senior Applied Scientist on this team you will:
- Serve as the technical leader in Machine Learning and Generative AI driving efforts within this team and across other teams.
- Lead end-to-end ML projects with high ambiguity scale and complexityfrom problem definition to production.
- Build optimize and deploy ML models into production partnering with software engineers to productionize solutions.
- Establish scalable automated processes for data analysis model development validation and serving.
- Apply strong knowledge of LLMs (prompt engineering fine-tuning RAG evaluation) to build production-grade GenAI applications.
- Analyze large-scale data sets to develop insights that increase traffic monetization and merchandise sales without compromising the shopper experience.
- Design and run A/B experiments and perform statistical analysis to measure impact and guide decisions.
- Research and prototype innovative ML and GenAI approaches bringing state-of-the-art techniques into production.
- Recruit mentor and grow Applied Scientists on the team.
About the team
Amazon is investing heavily in building a world-class advertising business. This team defines and delivers a collection of advertising products that drive discovery and sales. Our solutions generate billions in revenue and drive long-term growth for Amazons Retail and Marketplace businesses. We deliver billions of ad impressions millions of clicks daily and break fresh ground to create world-class products. We are a highly motivated collaborative and fun-loving team with an entrepreneurial spirit - with a broad mandate to experiment and innovate.
The Sponsored Products Search Sourcing Science (SPSSS) teams mission is to retrieve all relevant sponsored products in response to shopper queries serving billions of daily ad impressions and tens of millions of clicks helping shoppers discover useful and contextually relevant products while enabling advertisers to reach the right shoppers in the right context. To achieve this we build state-of-the-art capabilities spanning query shopper product and advertiser understanding as well as advanced retrieval targeting and ranking systems all powered by efficient large-scale data pipelines deep learning natural language processing (NLP) generative AI and multi-agent workflows. Its a high-impact technically exciting space where science directly translates into measurable outcomes for hundreds of millions of customers and millions of advertisers.
- 3 years of building machine learning models for business application experience
- PhD or Masters degree and 6 years of applied research experience
- Experience programming in Java C Python or related language
- Experience with neural deep learning methods and machine learning
- Experience in building speech recognition machine translation and natural language processing systems (e.g. commercial speech products or government speech projects)
- Experience with large scale machine learning systems such as profiling and debugging and understanding of system performance and scalability
- Masters degree or above in engineering statistics computer science mathematics or a related quantitative field
- Experience in patents or publications at top-tier peer-reviewed conferences or journals
- 3 years of building large-scale machine-learning infrastructure for online recommendation ads ranking personalization or search experience
- Experience in machine learning data mining information retrieval statistics or natural language processing or experience leading engineering teams as a mentor or tech lead
- Experience creating and delivering written and oral communications for technical and non-technical audiences
- Experience in data science business analytics business intelligence or similar experience in big data environments
- Thinks strategically but stays on top of tactical execution.
- Exhibits excellent business judgment; balances business product and technology very well.
- Experience in computational advertising.
- Experience in Large Language Models (LLMs).
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 for more information. If the country/region youre applying in isnt 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 WA SEATTLE - 167100.00 - 226100.00 USD annually
Required Experience:
Senior IC
About Company
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