The Google AI Residency Program is a 12-month research training role designed to jumpstart or advance your career in machine learning research.
Google AI Residency Program
Meet some of our current residents
By drawing on Google's state-of-the-art resources and research experience, we provide Residents in the program the skills that will enable them to tackle some of the world's greatest machine learning challenges. Meet some of our current Residents in the cohort!
Learn more about life as an AI Resident
Our Residents bring a diverse range of backgrounds and experiences from all over the world. Learn more from Residents past and present about what it’s like to be in the program.
In October 2015 we launched the Google Brain Residency, a 12-month program focused on jumpstarting a career for those interested in machine learning and deep learning research.
These are real stories from Googlers, interns, and alumni highlighting how they got to Google, what their roles are like, and even some tips on how to prepare for interviews.
Over the past year, the Residents familiarized themselves with the literature, designed and implemented experiments at Google scale, and engaged in cutting edge research.
I've spent the past year doing the Google Brain Residency Program. In this blog post I'll describe what the residency was like, what I worked on while here, and what I'm doing next.
Resident papers accepted to NIPS, 2018
Residents are encouraged to read papers, work on research projects, and publish in top-tier venues. These are the Resident papers that were accepted to NIPS this year.
Who should apply to the Google AI Residency program?
Ideal candidate either has a degree (BS, MS or PhD) or equivalent experience in STEM field such as CS, Math or Statistics. Having said that, we highly encourage candidates with non-traditional backgrounds and experiences from all over the world to apply to our program. Most importantly we are looking for individuals who are motivated to learn and have a strong interest and passion for machine learning research.
What can I expect from the program?
The residency program is similar to spending a year in a Master's or PhD program in machine learning. Residents are expected to read papers, work on research projects, and encouraged to publish in top-tier venues. By the end of the program, residents are expected to gain significant research experience in machine learning.
Where is the Residency Program based?
The Google AI Residency Program is primarily based in Mountain View, California. Residents will also have the opportunity to be based in New York, Cambridge (Massachusetts), Seattle (Washington), Montreal, Toronto, Zurich (Switzerland), Accra (Ghana) and Tel Aviv (Israel) depending on project fit and availability. Your recruiter will work with you to determine the best location for your work, though please also let them know if you have a location preference.
How do I apply and what does the application timeline look like?
Applications are open from October 9, 2018 to January 28, 2019, but we encourage you to submit your application as soon as possible. Visit g.co/airesidency/apply to apply.
Interviews (phone, video and/or onsite) will begin in November on a rolling basis until all positions are filled.
We are proposing multiple start dates over the course of 5 months (June to October) in 2019. Exact dates are yet to be finalized.
I’m interested in applying! What documents do I need to prepare in order to submit my application correctly?
What does the program curriculum look like?
Google AI Residents will spend the first two weeks of the program going through the Google Orientation sessions interlaced with introductory machine learning and deep learning classes. Each resident will then be assigned a short project to be completed within a week, during which longer term project and mentor assignments will take place in tandem.
How does the project and mentor assignment process work?
Project and mentor assignment will take place a few weeks after the program kicks off. This will give residents the opportunity to interact with various team members within research and learn more about what work the team is passionate about.
Projects chosen should ideally be a combination of short term and longer term projects. When choosing projects, residents will have the flexibility to select from a list of pre-proposed projects or propose their own ideas.
Mentors will be assigned based on the projects a resident decides to undertake. Each resident will have the opportunity to work with more than one mentor at a time, and mentors will rotate depending on the project lifecycle.