Applied scientist, eu intech consumer selection discovery, nintai

Applied Scientist, EU INTech Consumer Selection Discovery, NintAI Es esencial asegurarse de que cumple con los requisitos como solicitante para este puesto; por favor, lea atentamente la información a continuación. Job ID: 10450229 | Amazon Spain Services, S.L.U. 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—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 want 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 – analyse business problems, map them to science plans, and design and develop solutions from ideation to production. Off‐ice ownership of the full science lifecycle. Applied science with a research edge – deliver applied science solutions that drive measurable business impact while pushing the state of the art in computer vision and Generative AI. Hands‐on execution – thrive in building, experimenting, and shipping. Requirements A scientist who can independently analyse any business problem and design a rigorous science approach to solve it Strong hands‐on engineering skills – 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 of adapting 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 to production systems at Amazon scale and extending solutions 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 in patents or publications at top‐tier peer‐reviewed conferences or journals Experience programming in Java, C++, Python or a related language Experience building machine learning models or developing algorithms for business application PhD and experience in Computer Vision, Generative AI, Ranking, Deep Learning, Recommending, Systems, Natural Language Processing or related field Preferred Qualifications Experience using Unix/Linux Experience in professional software development Experience developing and implementing deep learning algorithms, particularly with respect to computer vision algorithms 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. Protecting your privacy and the security of your data is a longstanding top priority for Amazon. 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, please consult the Amazon disability accommodation policy. xqysrnh Amazon is an equal opportunity employer and does not discriminate on the basis of protected veteran status, disability, or other legally protected status. #J-18808-Ljbffr