The Artificial Intelligence (AI) Residency Program is a one-year research training position designed to give you hands-on experience with artificial intelligence research while working in Meta AI. This program is ideal for those interested in applying to PhD programs, publishing research papers, and maximizing their experience before applying or attending a graduate program in the designated field.
The program pairs you with AI Researchers to help guide your project. With the team, you will pick a research problem of mutual interest and then devise new machine learning techniques to solve it. The research will be communicated to the academic community through collaboration across Meta AI, academic papers and conferences (i.e. NeurIPS, ICML, ICLR, CVPR), and open-source code releases or product impact.
We encourage applications from people with technical backgrounds who hope to apply to a graduate program or would like more preparation before doing so. Prior experience in machine learning is certainly a strength, but we seek people with a passion for AI from a diverse range of backgrounds, including areas ostensibly unrelated to machine learning such as (but not limited to) math, physics, finance, economics, linguistics, computational social science, neuroscience, and bioinformatics. This is a full-time program that cannot be undertaken in conjunction with university study or a full-time job.
Learn how to perform research in deep learning and AI.
Understand prior work and existing literature.
Work with mentors to identify problem(s) of interest and develop AI techniques.
Translate ideas into practical code (in frameworks such as PyTorch).
Write up research results in the form of an academic paper or open-source projects.
Applications are open now
Application closes on January 18, 2022 at 5pm Pacific
New residents will start start on July 18, 2022
To learn more about what it's like to be an AI Resident, read our Q&A with two of our 2019 Facebook AI residents.
Will I be paid during the residency?
Yes. Residents are paid a competitive salary.
Is this a part-time program?
No. The Residency is only offered as a full-time position for one year. It is not possible to combine this with university study or a paid job.
What options will be open to me at the end of the program?
The residency is ideal preparation for applying to top graduate programs in machine learning. There are no conversions or full time roles associated with the program but Residents are welcome to interview for full-time positions across Meta after the program.
Can I do a longer Residency than 12 months?
The program base timeline is 12 months, with a possibility to extend for up to 12 months if project progress is deemed satisfactory and work authorization permits.
Can I do the Residency remotely?
No, Residents will be expected to work on-site at their allocated Facebook office, based on official COVID-19 company guidelines for office reopening. As of November 2021, all employees are expected to return to office by January 2022.
I have been out of school for several years. Am I eligible to apply?
Yes. We will consider applications from various backgrounds.
Can I be enrolled as a student at a university during the residency?
No, the residency can’t be completed simultaneously.
Can I work for a university or another employer during the residency?
No, the residency cannot be done simultaneously with other jobs.
Will I receive benefits during the Residency?
Yes, residents are eligible for most benefits, including medical. Residents are not eligible receive RSUs, annual bonuses, or merit increases. .
Will Facebook provide housing for the duration of this program?
No, but for those who are eligible we provide a competitive relocation package.
Is there a fee associated with this program?
There are no fees to participate in the program. The Residency pays a competitive salary and relocation for those that are eligible.
Questions about the Residency Program can be sent to firstname.lastname@example.org. Note that due to high volume, we are unable to answer questions about the status of your application.