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Machine Learning Intern - Edinburgh

Software Development
Ref: 841 Date Posted: Saturday 30 Dec 2017
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Machine Learning Intern, Edinburgh, 2018, 3-6 months

About the Role

We are looking for outstanding candidates to join our friendly, international team in central Edinburgh for 3-6 month Machine Learning internships in 2018. Internships are flexible in length to fit in with your university’s placement scheme. 

Our interns join one of our small agile teams at our development centre, launching and growing new initiatives for Amazon's global business. Your team will be involved in every aspect of the process - from idea generation, business analysis and technical design through to development and deployment across a variety of technologies - giving you a real sense of ownership. Together we build systems which meet high standards of performance and reliability and operate at massive scale.

Projects here include: 

  • Dynamic Merchandising - Personalised merchandising for Amazon on web, mobile and devices.
  • Dynamic Advertising - Personalised advertising (web, mobile and video) on third-party publisher sites.
  • Inherent Relationships - Worldwide media relationship data such as Series, Bibliography, Discography and AutoRip.
  • Talent Management - Inventing solutions to optimise employee talent across Amazon.

Amazon is a place where builders can build. Our internships offer exceptional opportunities for you to grow your technical and non-technical skills. From day one, you'll be working with experienced engineers, designers and applied scientists who love what they do.


You will be joining a high performing team that you will grow and innovate with. You will drive your own learning and development with guidance and coaching from your manager, buddy and colleagues around you. Not to mention the excellent long-term development prospects you’d expect from one of the world’s leading online businesses.

Basic Qualifications

On-track for a 2:1 or better degree in Computer Science, Machine Learning, Operational Research, Statistics or in a related quantitative field.

Essential skills

  • Understanding of, and practical experience with, machine learning/statistics/data science.
  • Enthusiasm for applying Machine Learning to business problems.
  • Computer science grounding in a range of algorithms and data-structures.
  • Proficient in an object-orientated programming language (Java, C++, C#, Python, etc.)
  • Excellent critical thinking skills, combined with the ability to present your beliefs clearly and compellingly in both verbal and written form.

Preferred Qualifications

Postgraduate study.

Personal qualities

  • Energy and willingness to formulate, test, and discard or revise many hypotheses.
  • Results oriented with a strong customer and business focus.
  • Ability to communicate and discuss technical topics with both technical and business audiences.
  • Innovative, flexible and self-directed, while also able to work within a team.
  • Ability to deal well with ambiguous and undefined problems.

We offer highly competitive internship salaries. This is your opportunity to experience a unique environment and spend 3-6 months with a passionate and international team who work hard, have fun and make history!

How to apply

All candidates must apply directly to Amazon via the link below.

Please note that we expect to experience a high volume of applications and we will fill positions as they become available, so we encourage you to apply early. Please include your academic transcript in your CV.

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.

All offers are conditional on references, verification of the right to work in the UK, and a successful background screening check. This check will include previous employment verification, qualification verification (if relevant) and a basic criminal check. Further details of this policy and procedure will be sent to you along with your conditional offer.

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