Senior Applied Scientist, Sponsored Products and Brands
Not Disclosed•Full-TimeOn-site
location_on301, Union Street, Central Business District, Belltown, Seattle, King County, Washington, 98101, United States
About the Team
The Sponsored Products and Brands team at Amazon Ads is re-imagining the advertising landscape through industry-leading generative AI technologies. We are revolutionizing how millions of customers discover products and engage with brands across Amazon.com and beyond. As a passionate group of innovators, we are dedicated to developing responsible and intelligent AI technologies that balance the needs of advertisers, enhance the shopping experience, and strengthen the marketplace.
You will join a newly-founded Global Optimization science team with a broad mandate to experiment and innovate. Our focus is on driving the growth of sponsored products ad experiences across non-US marketplaces. This charter gives us the flexibility to explore and apply scientific techniques to novel product problems, working backwards from emerging markets to reimagine Amazon's advertising stack from the ground up.
About the Role
This is your opportunity to be part of a small, high-impact team that prototypes, invents, and ships state-of-the-art solutions that will define the future of digital advertising. We are leveraging multilingual and multi-modal GenAI technologies—including semantic hash designs, LLMs, and more—to deliver solutions that scale to non-US marketplaces from day one.
The ideal candidate combines entrepreneurial drive with deep technical expertise, thriving in ambiguous, fast-moving environments where you define the path forward with minimal structure. Our team regularly goes from ideas on the whiteboard to production-grade experiments. Your Customer Obsession fuels your passion for translating science into real-world value for millions of advertisers and customers worldwide. Whether you're architecting scalable GenAI systems or optimizing multi-task recommendation engines, you will cut through complexity to find the solutions that deliver the most results. You are not just a scientist or just an engineer—you're a builder who sees the bigger picture and knows how to make it reality.
Hiring Process
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.
Work location
Work model: On-site
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Skills, education and keywords
Skills: Generative Ai, Artificial Intelligence, Semantic Hash Designs, LLMS, Machine Learning, Java, C++, Python, Neural Deep Learning, R.
Education: PhD or Master's degree with 5+ years of applied research experience; Master's degree with 5+ years of applied research experience.
Frequently asked questions about Senior Applied Scientist, Sponsored Products and Brands at Amazon
What does a Senior Applied Scientist, Sponsored Products and Brands at Amazon do?expand_more
A Senior Applied Scientist, Sponsored Products and Brands at Amazon is responsible for the following: Architect next-generation systems to replace legacy monolithic infrastructure with scalable, intelligent solutions; Pioneer breakthrough applied science in multi-modal GenAI applications for advertising; Drive end-to-end innovation from research ideation through production deployment at Amazon scale; and Lead cross-functional collaboration with product, engineering, and business teams to translate science into customer impact.
What are the requirements for this Senior Applied Scientist, Sponsored Products and Brands role?expand_more
Amazon is looking for candidates who meet the following requirements: 3+ years of building machine learning models for business application experience; PhD, or Master's degree and 5+ years of applied research experience; Experience programming in Java, C++, Python or related language; Experience with neural deep learning methods and machine learning; Experience with modeling tools such as R, scikit-learn, Spark MLLib, MxNet, Tensorflow, numpy, scipy etc.; and Experience with large scale distributed systems such as Hadoop, Spark etc..