About the Program: The Google AI Residency Program (formerly known as the Google Brain Residency Program) is a 12-month role designed to advance your career in machine learning research. Residents will work alongside distinguished scientists from various Research teams. The goal of the residency is to help residents become productive and successful AI researchers.
We created the Google Brain Residency Program in 2015, and we are now expanding it into a broader program that involves not just the Google Brain team, but a broader group of research teams doing machine learning research. Residents will have the opportunity to do everything from conducting fundamental research to contributing to products and services used by millions of people. We encourage our Residents to publish their work externally. Take a look at what some have done in previous years.
We are looking for people who want to learn to conduct machine learning research in collaboration with our researchers. You may have research experience in another field (e.g., mathematics, physics, bioinformatics, etc.) and want to apply machine learning to this area, or you may have limited research experience but, a desire to do more. Of course having machine learning research experience is great.
Current students will need to graduate from their current degree program before the residency begins. We encourage candidates from all over the world to apply. If a candidate requires a work visa, Google will explore what options are available on a case by case basis.
The Google AI Residency Program is primarily based in the Bay Area and is expanding to new locations in 2018. Depending on resident interests, project fit, and team needs, accepted residents may be based in locations outside of the Bay Area, including New York; Cambridge (Massachusetts); Montreal; and Toronto. Residents are expected to work on site.
To apply, please read all instructions below and submit the following required materials:
- Cover Letter
Your application should show evidence of proficiency in programming and in prerequisite courses, notable performance in competitions, or links to an open-source project that demonstrates programming and mathematical ability. Your application should present a strong interest in the field. This can be demonstrated through links to publications and blog posts, or implementations of one or more (even slightly) novel learning algorithms, including an explanation for what makes it novel.
Prepare the following documents to complete your application:
- Current CV (including links to GitHub, papers and/or blogs if applicable).
- Cover letter including a statement on why you think you’d be great for the Google AI Residency Program.
- Transcripts from your most recent degree.
Click on the “Apply Now” button on this page to provide the above required materials in the appropriate sections (PDFs preferred):
- In the “Resume Section:” attach an updated resume.
- In the “Optional Section:” attach your cover letter that includes a statement on why you think you’d be great for the Google AI Residency Program. This section is mandatory for the program even though it is optional, as noted on the website, for other jobs at Google.
- In the “Education Section:” attach a current unofficial or official transcript in English. (Under “Degree Status,” select “Now attending” to upload a transcript.)
Note: We will ask you to provide a Letter of Recommendation once you have passed an initial review. If so, please have your recommender submit their letter to firstname.lastname@example.org.
Questions? See our FAQ.There is always more information out there, and the Research and Machine Intelligence team has a never-ending quest to find it and make it accessible. We’re constantly refining our signature search engine to provide better results, and developing offerings like Google Instant, Google Voice Search and Google Image Search to make it faster and more engaging. We’re providing users around the world with great search results every day, but at Google, great just isn’t good enough. We’re just getting started.
- Learn and understand a large body of research in deep learning and/or machine learning algorithms.
- Work with research mentors to formulate research project(s) and/or novel application(s) of machine learning.
- Conduct research and publish it in competitive venues.
- Implement algorithms in TensorFlow.
- BA/BS degree in a STEM field such as Computer Science, Mathematics or Statistics, or equivalent practical experience.
- Completed coursework in calculus, linear algebra, and probability, or their equivalent.
- Experience with one or more general purpose programming languages, including but not limited to: C/C++ or Python
- Experience with machine learning or deep learning, applications of machine learning to NLP, computer vision, speech, systems, robotics, algorithms, optimization, on-device learning, social networks, economics, information retrieval, journalism, or health care.
- Research experience in machine learning or deep learning (e.g., links to open-source work or link to novel learning algorithms).
- Strong open-source project experience that demonstrates programming, mathematical, and machine learning abilities and interest.