Applied Scientist, EU International Technologies

As an Applied Scientist on this team, you will take on a key role in improving capabilities of the Amazon product search service, and ensure we offer top-quality recommendations for all our customers regardless of their location or language. Our ultimate goal is to help customers find the products they are searching for, and discover new products they would be interested in. We do so by developing components to improve query understanding, ranking of search results, and personalization - all covering a wide range of languages.

This is a rewarding role where you will be able to draw a clear connection between your work and how it improves the experience of millions of Amazon customers across the globe every day. You can also expect to have excellent opportunities, and ample support, for career growth, development, and mentorship.

Key job responsibilities

• Analyze the data and metrics resulting from traffic into Amazon's product search service
• Design, build, and deploy effective and innovative ML solutions to improve various components of the search stack, query understanding, ranking, and personalization.
• Evaluate the proposed solutions via offline benchmark tests as well as online A/B tests in production
• Publish and present your work at internal and external scientific venues in the fields of ML/NLP/IR

A day in the life

You will propose and explore publication-worthy innovation using ML/NLP/IR techniques, build ML models trained on terabytes of data, which are evaluated using both offline metrics as well as online metrics via A/B testing. You will then integrate these models into the production search engine that serves customers, closing the loop through data, modeling, application, and customer feedback. The chosen approaches for model architecture will balance business-defined performance metrics with the needs of millisecond response times.

About The Team

EU International Technologies is an organization focused on accelerating the EU Stores business by delighting customers and selling partners. The team's mission is to innovate locally and scale worldwide, fostering a world-class community of builders that delivers with speed and agility. EU INTech operates across domains including consumer discovery, search, selection, partner growth, pricing, sustainability, and marketplace expansion. The culture emphasizes collaboration, inclusion, technical excellence, big bets on high-impact projects, transparency, and long-term ownership - empowering engineers and scientists to solve complex problems at international scale.

Basic Qualifications

• Experience programming in Java, C++, Python or related language
• Knowledge of Machine Learning and LLM fundamentals, including transformer architecture, training/inference lifecycles, and optimization techniques
• Master's degree in a quantitative field such as statistics, mathematics, data science, business analytics, economics, finance, engineering, or computer science
• Fluency in written and spoken English (German is not required)

Preferred Qualifications

• Experience implementing algorithms using both toolkits and self-developed code
• Have publications at top-tier peer-reviewed conferences or journals
• Experience working on recommender systems or personalization within search, e-commerce, shopping, advertising or other related fields
• 1+ years of post-Master's hands-on experience (academic or industrial) building ML models
• Fluency in one or more languages other than English

Amazon is an equal opportunities employer. We believe passionately that employing a diverse workforce is central to our success. We make recruiting decisions based on your experience and skills. We value your passion to discover, invent, simplify and build. Protecting your privacy and the security of your data is a longstanding top priority for Amazon. Please consult our Privacy Notice ( to know more about how we collect, use and transfer the personal data of our candidates.

m/w/d

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Company – Amazon Development Center Germany GmbH

Job ID: A