At Amazon, we are committed to being the Earth's most customer-centric company. The European International Technology group (EU INTech) owns the enhancement 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 our own innovative new projects.

You will be joining the Tamale team to work on Haul. As part of EU INTech and Haul, Tamale strives to create a discovery-driven shopping experience using challenging machine learning and ranking solutions. You will be exposed to large-scale recommendation systems, multi-objective optimization, and state-of-the-art deep learning architectures, and you'll be part of a key effort to improve our customers' browsing experience by building next-generation ranking models for Amazon Haul's endless scroll experience.

We are looking for a passionate, talented, and inventive Scientist with a strong machine learning background to help build industry-leading ranking solutions. We strongly value your hard work and obsession to solve complex problems on behalf of Amazon customers.

Key job responsibilities
We look for applied scientists who possess a wide variety of skills. As the successful applicant for this role, you will work closely with your business partners to identify opportunities for innovation. You will apply machine learning solutions to optimize multi-objective ranking, improve discovery engagement through contextual signals, and scale ranking systems across multiple marketplaces. You will work with business leaders, scientists, and product managers to translate business and functional requirements into concrete deliverables, including the design, development, testing, and deployment of highly scalable distributed ranking services. You will be part of a team of scientists and engineers working on solving ranking and personalization challenges at scale. You will be able to influence the scientific roadmap of the team, setting the standards for scientific excellence. You will be working with state-of-the-art architectures and real-time feature serving systems.

Your work will improve the experience of millions of daily customers using Amazon Haul worldwide. You will have the chance to have great customer impact and continue growing in one of the most innovative companies in the world. You will learn a huge amount - and have a lot of fun - in the process!

Basic Qualifications

• Experience in building models for business application
• PhD, or a Master's degree and experience in CS, CE, ML or related field
• Experience in patents or publications at top-tier peer-reviewed conferences or journals
• Experience programming in Java, C++, Python or related language
• Experience developing and implementing deep learning algorithms, particularly with respect to computer vision algorithms

Preferred Qualifications

• Experience in any of the following areas: algorithms and data structures, parsing, numerical optimization, data mining, parallel and distributed computing, high-performance computing
• Experience in state-of-the-art deep learning models architecture design and deep learning training and optimization and model pruning
• Experience with popular deep learning frameworks such as Mx Net and Tensor Flow

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.