Facebook AI Research (FAIR) Residency Program


Deadline  : January 26, 2018

Type         : Full-time, paid

Duration :  One year (August 2018-August 2019)

Location  : Facebook Menlo Park and New York


The Facebook AI Research (FAIR) Residency Program is a one-year research training program with Facebook’s AI Research group, designed to give you hands-on experience of machine learning research. The program will pair you with a senior researcher or engineer in FAIR, who will act as your mentor. Together, you will pick a research problem of mutual interest and then devise new deep learning techniques to solve it.

The AI research residency experience is designed to prepare you for graduate programs in machine learning, or to kick-start a research career in the field. This is a full-time program that cannot be undertaken in conjunction with university study or a full-time job.


  • Bachelors degree in a STEM field such as Mathematics, Statistics, Physics, Electrical Engineering, Computer Science, or equivalent practical experience.
  • Completed coursework in: Linear Algebra, Probability, Calculus, or equivalent.
  • Coding experience in a general-purpose programming language, such as Python or C/C++.
  • Familiarity with a deep learning platform such as PyTorch, Caffe, Theano, or TensorFlow.
  • Ability to communicate complex research in a clear, precise, and actionable manner.

Preferred Qualifications

  • Research experience in machine learning or AI (as established for instance via publications and/or code releases).
  • Significant contributions to open-source projects, demonstrating strong math, engineering, statistics, or machine learning skills.
  • A strong track record of scholastic excellence

Application Process

To apply to the 2018 Facebook AI Residency Program, you will need to complete the application and submit the following items:

  1. CV/Resume (including links to GitHub, professional web-pages, publications, or blog-posts as applicable)
  2. Personal statement
  3. Academic grade transcript

Note: All materials must be in PDF format.

Click here for Application Form and Official Link