Description

　　This role is available across multiple locations in Germany (Munich, Berlin, Tübingen, Aachen). Amazon Internships have start dates throughout the year and can vary in length from 3-6 months for full-time. Please note these are not remote internships.

　　Are you a MS or PhD student interested in a 2024 Internship in the field of Applied Sciences? Are you interested in machine learning, deep learning, speech, robotics, computer vision, optimization, quantum computing, automated reasoning, or formal methods? If so, we want to hear from you! We are looking for scientists with interest in using a variety of domain expertise to invent, design and implement state-of-the-art solutions for never-before-solved problems.

　　At Amazon, you will grow into the high impact, visionary person you know you’re ready to be. Every day will be filled with developing new skills and achieving personal growth. How often can you say that your work changes the world? At Amazon, you’ll say it often. Join us and define tomorrow.

　　For more information on the Amazon Science community please visit the Science hub page: https://www.amazon.science/

　　If you’re interested in hearing more or have questions about Amazon Science internships, please feel free to join us for one of our upcoming informational sessions which you can sign up for via the ‘Events Calendar’ in our EMEA Science Intern landing page;

　　https://amazonscienceopportunities.splashthat.com/

　　Key job responsibilities

　　As an Applied Science Intern, you will own the design and development of end-to-end systems. You’ll have the opportunity to write technical white papers, create technical roadmaps and drive production level projects that will support Amazon Science. You will work closely with Amazon scientists, and other science interns to develop solutions and deploy them into production. You will have the opportunity to design new algorithms, models, or other technical solutions whilst experiencing Amazon’s customer focused culture. The ideal scientist must have the ability to work with diverse groups of people and cross-functional teams to solve complex business problems.

　　We are open to hiring candidates to work out of one of the following locations:

　　Aachen, DEU | Berlin, BE, DEU | Munich, BY, DEU | Tuebingen, DEU

　　Basic Qualifications

　　Basic qualifications

　　Enrolled in a PhD or Master's degree in Computer Science, Machine Learning, Engineering, Operations Research, Statistics or related fields

　　Experience in any programming language such as Python, Java, C++, or similar scripting and programming languages

　　Preferred Qualifications

　　Preferred qualifications

　　Publications at top-tier peer-reviewed conferences or journals

　　Experience in design of experiments and statistical analysis

　　Experience implementing algorithms using toolkits and self-developed code

　　Experience in solving business problems through machine learning, data mining and statistical algorithms

　　Familiar with the core undergraduate curriculum of computer science

　　Technical fluency; comfort understanding and discussing architectural concepts and algorithms, schedule trade-offs and new opportunities with technical team members

　　Excellent critical thinking skills, combined with the ability to present your beliefs clearly and compellingly in both verbal and written form

　　Amazon values knowledge of Accessibility in relation to its products, devices, services, websites or environments, so as to be usable by people with disabilities

　　Previous corporate work experience is not required

　　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.

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