Amazon's EU International Technology (EU INTech) organisation is creating new ways for customers to discover products through innovative customer experiences. Our team lead AI-native practices to make the path to product effortless, globally — experiment fast, grow our people, and deliver what customers feel.
We are a science and engineering team within EU INTech, responsible for designing and developing AI/ML science solutions. We innovate on the frontlines of customer experience WW across different categories: Healthcare, Everyday Essentials, Groceries, Amazon Haul. We work across the full customer journey from search to post-purchase. We are located in the Madrid Technical Hub.
We are looking for an Applied Scientist who is passionate about solving highly ambiguous and challenging problems at global scale. This is a hands-on, end-to-end applied science role where you will own the full lifecycle of science solutions — from business problem analysis and science plan design, through development and experimentation, to production deployment. We are looking for AI/ML experts with knowledge on ranking, computer vision, recommendation systems, search, and customer experience design.
What makes this role unique:
- End-to-end ownership – You will analyse business problems, map them to science plans, and design and develop solutions from ideation to production. We are owners of the full science lifecycle.
- Applied science with a research edge – While our focus is on delivering applied science solutions that drive measurable business impact, our team actively pushes the state of the art in areas such as computer vision and Generative AI.
Hands-on execution – We need scientists who thrive in building, experimenting, and shipping.
What We're Looking For
- A scientist who can independently analyse any business problem and design a rigorous science approach to solve it
- Strong hands-on engineering skills — you build and ship, not just theorise
- Deep expertise in one or more of: computer vision, generative AI, recommendation systems, ranking, or NLP
- Experience taking ML models from research to production at scale
- Comfort with ambiguity and the ability to structure complex, undefined problems
- A passion for customer-centric innovation and measurable impact
- A strong communicator capable to adapt the message from a science audience, to engineering or leadership
Key job responsibilities
- Analyse complex business problems and translate them into well-defined science plans with clear milestones and success criteria
- Design, develop, and deliver ML/AI models end-to-end — from research and prototyping through to production systems at Amazon scale and extending solutions going beyond the state of the art
- Work with state-of-the-art models in computer vision, ranking and generative AI to power new customer experiences globally
- Own major science challenges for the team, driving solutions from ideation through experimentation to production deployment
- Collaborate with a variety of roles and partner teams around the world to deliver integrated solutions
- Influence scientific direction and best practices across the team.
- Maintain high quality standards on team deliverables
- Contribute to expanding the state of the art in computer vision, ranking and GenAI through publications and internal knowledge sharing
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