Applied Scientist, Products

Job :  |  Services LLC

About Sponsored Products and Brands:
The Sponsored Products and Brands 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  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.

About our team:
The SPB Offsite team builds solutions to extend campaigns to reach customers off the store and extend shopping experiences on third‑party sites where shoppers search and discover products. We use industry‑leading machine learning, high‑scale low‑latency systems, and AI technologies to create better sponsored customer experiences off the store. This role will have deep interest in building the next innovations in ad tech and shopping wherever shoppers go.

You will work with external and internal partners to connect ad tech systems, understand customers, and drive results  are a deeply technical leader who operates with a GenAI first approach to product, engineering, and science‑based solutions.

• Drive end‑to‑end Machine Learning projects that have a high degree of ambiguity, scale, and 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 machine learning models, perform proof‑of‑concept, experiment, optimize, and deploy your models into production; work closely with software engineers to assist in product ionizing your ML models.
• 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.
• Research new and innovative machine learning approaches.

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. The solutions generate billions in revenue and drive long‑term growth for Amazon’s Retail and Marketplace businesses. The team delivers billions of ad impressions, millions of clicks daily, and breaks 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.

• 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 algorithms and data structures, parsing, numerical optimization, data mining, parallel and distributed computing, high‑performance computing

• Experience in professional software development
• Experience in search advertising, search marketing, performance advertising, or similar digital advertising
• Strong technical fluency in Generative AI
• Deep understanding of large language models (LLMs),…