Sr Principal Scientist, EU INTech

The Amazon International Technology (INTech) team owns the discovery and delivery of Amazon's engineering to all the varied customers and cultures of the world. We do this through a combination of partnerships with other Amazon technical teams and innovative new projects. We make sure that each of our websites is a thoughtful combination of Amazon known best practices and unique last-mile engineering driven by each country's customers' needs. The work spans the technology stack from science to front-end customer experience to back-end core services.

INTech Europe is a technology team focused on accelerating the EU business while deploying tech solutions WW wherever applicable.

EU INTech operates at a unique intersection: worldwide-scale science constrained by EU-specific realities — 10+ languages, 10+ marketplaces. Our science problems — localization, customer understanding, multilingual catalogue intelligence or visual content — are core primitives to serve our WW customers.

This role is ideally located in Madrid or Luxembourg, but we will also consider London as an additional location.

Key job responsibilities
As a Senior Principal Scientist, you will shape the definition and vision for science across INTech Europe and beyond. Leveraging your expertise in both theory and practice in Natural Language Processing / Understanding, Machine Learning, and Computer Vision, you will act as a strategic advisor to the EU Stores' leadership team and a scientific leader whose influence reaches across the worldwide International Stores Technology community.

You will:

• Own the science vision and strategy for EU INTech, setting the bar for scientific excellence across a community of scientists spanning Applied Science, Research Science, and Economics, working on GenAI, NLP/NLU, ML, and computer vision applied to e-commerce at scale.

• See around corners and identify business problems that will impact our customers' and selling partners' experience. You will explore problems that are unique and unsolved, proposing and delivering solutions that translate scientific research and business judgment into products that improve the customer and employee experience.

• Drive science as a pillar of EU INTech's biggest bets — where you will shape and prototype reusable science capabilities for multilingual evaluation and locale-specific model customization.

• Set and hold the bar for Responsible AI, ensuring scientific and ethical rigour is embedded as a prerequisite in how we build and launch AI across the organization.

• Lead writing efforts of notable internal and external publications that validate originality, inspire new lines of research, and elevate internal and external science communities.

• Mentor and develop senior scientists, building the next generation of science leadership across the organization.

Qualificações básicas

Basic qualifications

• PhD in Computer Science, Engineering, Mathematics, or a related field.
• Demonstrable of experience building machine learning models
• A track record of world-class publication in related disciplines.
• Demonstrated expertise in both theory and practice in Natural Language Processing / Understanding, Machine Learning, and Computer Vision.
• Hands-on experience with a broad range of qualitative and quantitative research methods.
• Experience multi-tasking and taking input from various teams and sources to scope research work with effective prioritization.
• Excellent verbal and written communication skills with demonstrated experience effectively advising senior management and executives.

Qualificações preferenciais

Preferred qualifications

• Experience applying GenAI / LLMs to production systems at scale.
• Experience operating science in a regulated, privacy-constrained environment (e.g. GDPR, multi-market).
• Exceptional ability to present complex technical information in a clear and concise manner to a variety of audiences, including large technical audiences, senior management, and customers.
• Exceptional relationship skills, including the ability to discover true requirements, recommend alternative technical and business approaches, and lead engineering efforts to meet timelines with optimal solutions.
• Track record of developing intellectual property.
• Participation on academic program committees and open-source programs.
• Hands-on programming experience including writing production-quality code, building prototypes, and reviewing code with applied scientists and engineers.

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