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Amazon

Applied Scientist, Sponsored Products and Brands

OnsiteOther rolesNot yet verified

United States, WA, Seattle; United States, NY, New York; United States, WA, SEATTLE; United States, CA, Palo Alto

Original posting date
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Nov 2, 2026

Saved job description

About Sponsored Products and Brands

The Sponsored Products and Brands (SPB) team at Amazon Ads is re-imagining the advertising landscape through 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.

About our team

The General Shopping Intelligence (GSI) team is a highly motivated, collaborative, and fun-loving group with a strong entrepreneurial spirit and bias for action. We provide advanced real-time machine learning services that connect shoppers with the right ads across all platforms and surfaces worldwide. Through deep understanding of both shoppers and products, we help shoppers discover new products they love, enable advertisers to reach their customers most efficiently, and help Amazon continuously innovate on behalf of all customers.

We are seeking a motivated Applied Scientist who loves to innovate at the intersection of customer experience, deep learning, generative AI and high-scale machine learning systems. 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.

Key job responsibilities

As an Applied Scientist, you will:

* Leverage Generative AI and Large Language Models (LLMs) to mine complex behavioral data, deriving deep, actionable shopper insights that identify customer experience gaps and unlock new business opportunities.

* Design and develop scalable machine learning and GenAI models focused on shopper intent and preference modeling, ensuring a rapid path from prototype to production.

* Partner closely with engineering teams to architect and deploy end-to-end GenAI solutions into production, integrating advanced insights directly into real-time, customer-facing systems.

* Drive the scalability, efficiency, and automation of large-scale model training and real-time inference systems, pioneering the LLM infrastructure required to support next-generation GenAI workloads at Amazon Ads scale.

* Design and run rigorous A/B experiments to quantify the business and customer impact of GenAI-driven shopper insights, performing advanced statistical analysis to guide iterative production rollouts.

* Conduct applied research in novel generative AI techniques (e.g., fine-tuning, RAG, agentic workflows) to optimize the shopper experience and drive performance across all aspects of the Sponsored Products and Brands business.

Requirements: - 3+ years of building models for business application experience

- PhD, or Master's degree and 4+ years of CS, CE, ML or related field experience

- Experience programming in Java, C++, Python or related language

- Experience in any of the following areas: algorithms and data structures, parsing, numerical optimization, data mining, parallel and distributed computing, high-performance computing

Location & listing notes

Locations describe the saved posting and do not confirm residence eligibility. Confirm qualifications, travel, restrictions, and availability with the employer.

Source-listed locations: US, Seattle, Washington; US, New York, New York; US, SEATTLE, Washington; US, Palo Alto, California.

Listed states: CA, NY, WA.

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