It's been three months into my Google AI residency journey and sometimes I'm asked about how I became a Google AI resident. I thought it could be a good idea to write it down as my personal reflection. Readers who's interested in applying this program in the future hopefully can find it helpful as a reference point.
I'd admit that I didn't know about this program until early 2019, but I've been generally thinking about joining Google to deepen my understanding of machine learning via direct hands-on AI research. Unfortunately, the application window of then-current season had been closed so I remember I made a reminder note for myself. Besides the reminder, I did find some relevant blog posts, e.g., this one from the past residents on residency application and the overall experience.
One most important document is the cover letter. Although it's optional to most of the industry jobs, AI residency application specifically requires it and even demand applicants to answer certain questions in the letter. I used this post as my guide, which covers how to write such a cover letter with good quality.
Since many people potentially from different backgrounds, e.g., recruiters, reserchers, are gonna look at your cover letter, it's always a good idea to make your past reserach experience easy to understand. To do that, I even asked my friend who's from humanities background to review it and iterated a few rounds until it sounds logical to her.
I didn't hear about anything until late Feburary. During the wait, I was also interviewing a SWE role (focused on Machine Learning) at Google Search. This application moved along quickly - I was already hiring approved by the hiring committee in the middle of January and started team matching. I was debating whether I should continue the wait for AI residency result if my team matching at Google Search was successful. As it turned out, the team matching didn't move as fast (partially because my recruiter is manily familiar with East coast hiring situation while my intened location is on the West coast) and I got my first email from AI residency informing me that I got a research interview opportunity.
Research interview is intended to assess one's research experience and communication effectiveness. Since I've iterated many times in the cover letter writing phase, this really saved me a lot of time in preparation. I used to work with Graph Convolutional Neural Network (GCNN) and was asked to explain it. I remember my explanation started from CNNs which work on regular grids (e.g., images) and gradually extended to graph (irregular grids), that made my interviewer get the point immediately.
The recruiter knew I was moving along the SWE application as well, which seemed to expedite the residency interview process. In the middle of March, I was told they were happy to make an offer to me as an AI resident. On the SWE side, the team matching almost stagnated after the COVID crisis became real. Now I have to decide if I wanted to wait for Google Search to find a team for me.
After talking to a few ex-AI-residents whom I share similar background with (e.g., engineering PhD), I realized that it sounds like a good place for me to be in by experiencing AI research at multiple teams instead of diving into a dedicated team doing engineering directly if my goal is to broaden my AI experience and skills. I talked to myself that I can come back to SWE if eventually I realize AI research isn't fun for me. So regret minimization helped me make the decision (let's see how this decision turns out).
2020 October I officially started as one of the ~40 residents hired globally this year - the 5th Google AI cohort. Being in Google Research certainly brings back many my old feelings of being at MIT - great people, enormous resources and wild imagination. I'm hopeful and grateful for the wonderful year to come. Although busy, I'll try to make time to add posts on the residency experience. Stay tuned.