Offers “Amazon”

Expires soon Amazon

2020 Machine Learning Internship - Alexa Shopping

  • Internship
  • Cambridge (Cambridgeshire)

Job description


The Alexa Shopping Science team in Cambridge is looking for Applied Science Interns for summer 2020.

As an applied scientist in Alexa Shopping, you will be responsible for the research, design and development of new machine learning technologies for voice-based and multimodal experiences on Alexa. You will be working with top scientists and engineers, as well as with product teams and other research partners, both locally and abroad. Your work will combine machine learning, data mining, systems and software development, exploration of new technologies, as well as working towards publications and presentations at top scientific conferences.

The team you will be working with has expertise in probabilistic and Bayesian modeling, Gaussian processes, deep learning, user modeling, natural language processing and other related fields. We employ all these technologies to continually improve the experience of Alexa customers, focusing on the shopping domain.


· Ability to convey rigorous mathematical concepts and considerations to non-experts.
· Ability to distil problem definitions, models, and constraints from informal business requirements; and to deal with ambiguity and competing objectives.
· Strong software development skills.

By submitting your resume and application information, you authorize Amazon to transmit and store your information in the Amazon group of companies' world-wide recruitment database, and to circulate that information as necessary for the purpose of evaluating your qualifications for this or other job vacancies.

Ideal candidate profile


· Current enrollment in a degree-granting college or university working towards a PhD in Machine Learning, Natural Language Processing, Data Mining, Statistics, Applied Mathematics, or a related field.
· Hands on experience in machine learning, natural language processing and applications, in particular one or more of: Bayesian machine learning, deep learning, crowdsourcing, user modelling.
· At least one refereed academic publication in these areas.
· Good coding skills. Experience in Python is a plus.
· Good communication skills and the ability to work in a team.