- Master's degree in computer science, mathematics, statistics, machine learning or equivalent quantitative field Amazon's International Technology org in EU (EU INTech) is creating new ways for Amazon customers discovering Amazon catalog through new and innovative Customer experiences.
Our vision is to provide the most relevant content and CX for their shopping mission.
We are responsible for building the software and machine learning models to surface high quality and relevant content to the Amazon customers worldwide across the site.
The team, mainly located in Madrid Technical Hub, London and Luxembourg, comprises Software Developers, ML Engineers, Applied Scientists, Product Managers, Technical Product Managers, and UX Designers who are experts in several areas of ranking, computer vision, recommendations systems, Search as well as CX.
Are you interested in how the experiences that fuel Catalog and Search are built to scale to customers worldwide?
Are you interested in how we use state of the art AI to generate and provide the most relevant content?
Key Job Responsibilities We are looking for Applied Scientists who are passionate about solving highly ambiguous and challenging problems at a global scale.
You will be responsible for major science challenges for our team, including working with text to image and image to text state of the art models to scale and enable new Customer Experiences worldwide.
You will design, develop, deliver, and support a variety of models in collaboration with various roles and partner teams around the world.
You will influence scientific direction and best practices and maintain quality on team deliverables.
- Knowledge of core undergraduate curriculum of computer science 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.
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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.
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