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Job description
Description Amazon's advertising business has grown exponentially over the past years, helping connect sellers and vendors to shoppers who may be interested in their products. Our ad products are strategically important to our Retail and Marketplace businesses driving long term growth. We deliver billions of ad impressions and millions of clicks daily and are breaking fresh ground to create world-class products that leverage state of the art AI technologies.
Amazon's advertising business has grown exponentially over the past years, helping connect sellers and vendors to shoppers who may be interested in their products. Our ad products are strategically important to our Retail and Marketplace businesses driving long term growth. We deliver billions of ad impressions and millions of clicks daily and are breaking fresh ground to create world-class products that leverage state of the art AI technologies.
The Sponsored Products and Brands team is seeking a Principal Applied Scientist to lead the development and implementation of generative AI solutions for ad allocation and ranking on Amazon search pages. This role will be instrumental in revolutionizing how we match ads with customer intent and shopping behavior.
Key job responsibilities
Design and develop novel generative AI architectures for real-time ad allocation, focusing on both efficiency and effectiveness at massive scale
Lead research initiatives in applying large language models and multimodal AI to understand deep semantic relationships between ads, queries, and user behavior
Create innovative approaches to leverage GenAI for dynamic ad placement optimization while maintaining strict latency requirements
Collaborate with cross-functional teams to integrate GenAI solutions into existing advertising systems
Author research papers and technical documentation, contributing to the broader scientific community
Basic Qualifications
PhD in Computer Science, Applied Mathematics, Statistics or a closely related field of study.
8+ years of experience applying ML to solve complex problems for large-scale applications.
Preferred Qualifications
Ability to translate informal customer requirements into problem definitions, dealing with ambiguity and competing objectives.
Demonstrated leadership abilities, especially with cross-disciplinary efforts.
Hands on experience building machine learning models - from theoretical and application to real-world-problems perspectives.
Deep knowledge of statistical modeling techniques, scientific thinking, and the ability to apply these skills to real-world applications.
Deep business and technical vision.
Prior experience in online advertising or search ranking
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 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
USA, NY, New York - 218,800.00 - 295,900.00 USD annually
USA, WA, SEATTLE - 198,900.00 - 269,000.00 USD annually
Company
Amazon.com Services LLC
Job ID: A
#J-18808-Ljbffr
Worksite address
new york, NY, 10261, US
Who can apply
Review the original listing for work authorization, qualifications and employer requirements.