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Applied Scientist, EU INTech Consumer Selection Discovery, NintAI
Amazon Spain Services, S.L.U. —Madrid, Madrid provincia
- Jornada completa
- Doctorado
- Investigación
- Java
8d

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Amazon Spain Services, S.L.U. —Madrid, Madrid provincia
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…
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Applied Scientist, EU INTech Consumer Selection Discovery, NintAI
Amazon Spain Services, S.L.U. —Madrid, Madrid provincia
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…
8d

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Applied Scientist, EU INTech Consumer Selection Discovery, NintAI

Amazon Spain Services, S.L.U. -
Madrid, Madrid provincia

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Detalles del empleo

Jornada completa
Hace 8 días

Cualificaciones

Doctorado
Visión artificial
Investigación
Java
C++
Deep learning
NLP
UX
Desarrollo de software
Linux
Inteligencia artificial
Python

Descripción completa del empleo

DESCRIPTION

Amazon's EU International Technology (EU INTech) organisation is creating new ways for customers to discover products through innovative customer experiences. We are a science-only team within EU INTech, responsible for designing and developing AI/ML science solutions that support business needs across Amazon's global search and discovery experiences. Our mission is to make Amazon navigation easier for customers worldwide. We achieve this through two strategic pillars: making Amazon navigation more visual and improving Amazon navigation with more inspiring discovery tools and narrowing navigation.

To support this vision, we build and deploy AI/ML models that surface the most relevant content to hundreds of millions of Amazon customers worldwide. Our team comprises Applied Scientists and we partner with other teams, collaborating with ML Engineers, Software Developers, Product Managers, Technical Product Managers, and UX Designers. We are located in the Madrid Technical Hub.

We are looking for Applied Scientists who are 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 are we 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

BASIC QUALIFICATIONS

Experience programming in Java, C++, Python or related language
Experience in building models for business application
PhD and experience in Computer Vision, Generative AI, Ranking, Deep Learning, Recommending
Systems, Natural Language Processing or related field
Experience in patents or publications at top-tier peer-reviewed conferences (CVPR, SIGIR, ICCV,
NeurIPS, RecSys, …) or journals

PREFERRED QUALIFICATIONS

Experience using Unix/Linux
Experience in professional software development

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 (https://www.amazon.jobs/en/privacy_page) to know more about how we collect, use and transfer the personal data of our candidates.

Our inclusive culture empowers Amazonians to deliver the best results for our customers. If you have a disability and need a workplace accommodation or adjustment during the application and hiring process, including support for the interview or onboarding process, please visit https://amazon.jobs/content/en/how-we-hire/accommodations for more information. If the country/region you’re applying in isn’t listed, please contact your Recruiting Partner.

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