Applied Scientist, EU International Technologies

Role overview

This position is for an Applied Scientist working on improving Amazon’s product search experience across different countries and languages. The focus is on making search results and recommendations more relevant so customers can more easily find what they want and discover products they may like.

The work centers on building better query understanding, search ranking, and personalization systems for a multilingual environment. The impact is broad, with direct influence on the experience of millions of customers worldwide.

There is also strong support for professional development, mentoring, and long-term career growth.

What you will do

• Study traffic data and performance metrics from Amazon’s product search service.
• Develop, implement, and launch ML-based solutions that improve query understanding, ranking, and personalization across the search stack.
• Test ideas using offline evaluation methods and live A/B experiments in production.
• Share results through internal and external scientific publications and presentations in machine learning, NLP, and information retrieval.

Day-to-day work

You will explore new research ideas with machine learning, natural language processing, and information retrieval methods, train models on very large datasets, and measure performance through both offline and online experiments. Your models will then be integrated into the live search system, creating a full loop from data analysis to modeling, deployment, and customer feedback.

The work requires balancing business goals with strict latency needs, including millisecond-level response times.

About the team

EU International Technologies supports the EU Stores business by improving customer and partner experiences. The group works on discovery, search, selection, partner growth, pricing, sustainability, and marketplace expansion. The culture is built around collaboration, inclusion, technical excellence, transparency, ambitious high-impact work, and long-term ownership.

Basic qualifications

• Programming experience in Java, C++, Python, or a similar language.
• Strong understanding of machine learning and LLM fundamentals, including transformer architectures, training and inference workflows, and optimization approaches.
• A master’s degree in a quantitative discipline 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 with both established toolkits and custom-built code.
• Publications in top-tier peer-reviewed conferences or journals.
• Background in recommender systems or personalization for search, e-commerce, shopping, advertising, or similar areas.
• At least 1 year of post-master’s hands-on experience, either academic or industrial, in building ML models.
• Ability to work in one or more languages other than English.

Equal opportunity and privacy

The employer is committed to equal opportunity and evaluates candidates based on experience and skills. A diverse workforce is considered essential to success. Candidate privacy and data security are treated as a high priority.

Applicants requiring disability-related accommodations or adjustments during the hiring process, including interview or onboarding support, can request assistance through the company’s accommodation process.

Additional information

The role is described with inclusive language, including the marker m/w/d.