Artificial Intelligence Internship Program at Facebook 2019

Facebook is offering the Artificial Intelligence (AI) Residency Program in New York City, which is a one-year research training position designed to give you hands-on experience with machine learning research while working in Facebook artificial intelligence groups. The program will pair you with an AI Researcher and Engineer who will both guide your project. As a team, you will pick a research problem of mutual interest and then devise new deep learning techniques to solve it. The research will be communicated to the academic community by submitting papers to top academic venues as well as open-source code releases. The AI Residency experience is designed to prepare you for graduate programs in machine learning or to kickstart a career in the field. This is a full-time program that cannot be undertaken in conjunction with a university study or a full-time job. 

Responsibilities:

1. Learn how to perform research in deep learning and AI
2. Understand prior work and existing literature
3. Work with mentors to identify problem(s) of interest and develop novel AI techniques
4. Translate ideas into practical code 
5. Write up research results in the form of an academic paper or open-source project

Minimum qualifications:

1. Coding experience in a programming language
2. Knowledge in learning platforms 
3. Must obtain work authorization in the country of employment at the time of hire, and maintain ongoing work authorization during employment

Preferred qualifications:

1. Bachelor degree in a STEM field such as Mathematics, Statistics, Physics, Electrical Engineering, Computer Science, or equivalent practical experience
2. Completed coursework in Linear Algebra, Probability, Calculus, or equivalent
3. Research experience in machine learning or AI (as established for instance via publications and/or code releases)
4. Significant contributions to open-source projects, demonstrating strong math, engineering, statistics, or machine learning skills
5. Ability to communicate complex research in a clear, precise, and actionable manner