Applied Scientist, Sponsored Product Search Relevance
Applied Scientist, Sponsored Product Search Relevance
Posted on :
13-06-2025
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1 Vacancy
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Job Description
Amazon Advertising is one of Amazons fastest growing and most profitable businesses responsible for defining and delivering a collection of advertising products that drive discovery and sales. Our products and solutions are strategically important to enable our Retail and Marketplace businesses to drive long-term growth. We deliver billions of ad impressions and millions of clicks and break fresh ground in product and technical innovations every day!
The Search Relevance team parses billions of ads to surface the best ad to show to Amazon shoppers. The team strives to understand customer intent and identify relevant ads that enable them to discover new and alternate products. This also enables sellers on Amazon to showcase their products to customers which might be buried deeper in the search results. By showing the right ads to customers at the right time this team improves the shopper experience increase advertiser ROI and improves long-term monetization. This is a talented team of machine learning scientists and software engineers working on complex solutions to understand the customer intent and present them with ads that are not only relevant to their actual shopping experience but also non-obtrusive. This area is of strategic importance to Amazon Retail and Marketplace business driving long term growth.
As an Applied Scientist on this team you will:
- Explore and research deep learning methods in natural language processing large language model vision-language model and generative AI driving innovation in customer experience.
- Drive end-to-end deep learning projects that have a high degree of ambiguity scale complexity.
- Perform hands-on analysis and modeling of enormous data sets to develop insights that increase traffic monetization and merchandise sales without compromising the shopper experience.
- Build and deploy transformer-based models including LLMs and VLMs for both online and offline use cases. Develop proof-of-concepts run experiments optimize architectures and partner closely with engineering teams to productionize models at scale.
- Run A/B experiments gather data and perform statistical analysis.
- Establish scalable efficient automated processes for large-scale data analysis machine-learning model development model validation and serving.
- Recruit Applied Scientists to the team and provide mentorship.
Why you will love this opportunity: 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.
Impact and Career Growth: You will invent new experiences and influence customer-facing shopping experiences to help suppliers grow their retail business and the auction dynamics that leverage native advertising; this is your opportunity to work within the fastest-growing businesses across all of Amazon! Define a long-term science vision for our advertising business driven from our customers needs translating that direction into specific plans for research and applied scientists as well as engineering and product teams. This role combines science leadership organizational ability technical strength product focus and business understanding.
Team video
- Masters degree in computer science mathematics statistics machine learning or equivalent quantitative field
- Experience programming in Java C Python or related language
- Experience with SQL and an RDBMS (e.g. Oracle) or Data Warehouse
- Experience implementing algorithms using both toolkits and self-developed code
- Have publications at top-tier peer-reviewed conferences or journals
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.
Our compensation reflects the cost of labor across several US geographic markets. The base pay for this position ranges from $129400/year in our lowest geographic market up to $212800/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 This position will remain posted until filled. Applicants should apply via our internal or external career site.
The Search Relevance team parses billions of ads to surface the best ad to show to Amazon shoppers. The team strives to understand customer intent and identify relevant ads that enable them to discover new and alternate products. This also enables sellers on Amazon to showcase their products to customers which might be buried deeper in the search results. By showing the right ads to customers at the right time this team improves the shopper experience increase advertiser ROI and improves long-term monetization. This is a talented team of machine learning scientists and software engineers working on complex solutions to understand the customer intent and present them with ads that are not only relevant to their actual shopping experience but also non-obtrusive. This area is of strategic importance to Amazon Retail and Marketplace business driving long term growth.
As an Applied Scientist on this team you will:
- Explore and research deep learning methods in natural language processing large language model vision-language model and generative AI driving innovation in customer experience.
- Drive end-to-end deep learning projects that have a high degree of ambiguity scale complexity.
- Perform hands-on analysis and modeling of enormous data sets to develop insights that increase traffic monetization and merchandise sales without compromising the shopper experience.
- Build and deploy transformer-based models including LLMs and VLMs for both online and offline use cases. Develop proof-of-concepts run experiments optimize architectures and partner closely with engineering teams to productionize models at scale.
- Run A/B experiments gather data and perform statistical analysis.
- Establish scalable efficient automated processes for large-scale data analysis machine-learning model development model validation and serving.
- Recruit Applied Scientists to the team and provide mentorship.
Why you will love this opportunity: 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.
Impact and Career Growth: You will invent new experiences and influence customer-facing shopping experiences to help suppliers grow their retail business and the auction dynamics that leverage native advertising; this is your opportunity to work within the fastest-growing businesses across all of Amazon! Define a long-term science vision for our advertising business driven from our customers needs translating that direction into specific plans for research and applied scientists as well as engineering and product teams. This role combines science leadership organizational ability technical strength product focus and business understanding.
Team video
- Masters degree in computer science mathematics statistics machine learning or equivalent quantitative field
- Experience programming in Java C Python or related language
- Experience with SQL and an RDBMS (e.g. Oracle) or Data Warehouse
- Experience implementing algorithms using both toolkits and self-developed code
- Have publications at top-tier peer-reviewed conferences or journals
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.
Our compensation reflects the cost of labor across several US geographic markets. The base pay for this position ranges from $129400/year in our lowest geographic market up to $212800/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 This position will remain posted until filled. Applicants should apply via our internal or external career site.
Employment Type
Full-Time
Key Skills
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