Now that the deadline has arrived, I wanted to share some general feedback for the applicants and some general impressions for everyone in the space about the job market:
My number one recommendation for everyone is to work on more legible projects and outputs. A super low-hanging fruit for >50% of the applications would be to clean up your GitHub profiles or to create a personal site. Make it really clear to us which projects you’re proud of, so we don’t have to navigate through a bunch of old and out-of-use repos from classes you took years ago. We don’t have much time to spend on every individual application, so you want to make it really easy for us to become interested in you. I realize most people don’t even know how to create a GitHub profile page, so check out this guide.
We got 70 responses and will send out 10 invitations for interviews.
We rejected a reasonable number of decent candidates outright because they were looking for part-time work. If this is you, don’t feel dissuaded.
There were quite a few really bad applications (...as always): poor punctuation/capitalization, much too informal, not answering the questions, totally unrelated background, etc. Two suggestions: (1) If you’re the kind of person who is trying to application-max, make sure you actually fill in the application. A shitty application is actually worse than no application, and I don’t know why I have to say that. (2) If English is not your first language, run your answers through ChatGPT. GPT-3.5 is free. (Actually, this advice is for everyone).
Between 5 and 10 people expressed interest in an internship option. We’re going to think about this some more. If this includes you, and you didn’t mention it in your application, please reach out.
Quite a few people came from a data science / analytics background. Using ML techniques is actually pretty different from researching ML techniques, so for many of these people I’d recommend you work on some kind of project in interpretability or related areas to demonstrate that you’re well-suited to this kind of research.
Remember that job applications are always noisy. We almost certainly made mistakes, so don’t feel discouraged!
Now that the deadline has arrived, I wanted to share some general feedback for the applicants and some general impressions for everyone in the space about the job market:
My number one recommendation for everyone is to work on more legible projects and outputs. A super low-hanging fruit for >50% of the applications would be to clean up your GitHub profiles or to create a personal site. Make it really clear to us which projects you’re proud of, so we don’t have to navigate through a bunch of old and out-of-use repos from classes you took years ago. We don’t have much time to spend on every individual application, so you want to make it really easy for us to become interested in you. I realize most people don’t even know how to create a GitHub profile page, so check out this guide.
We got 70 responses and will send out 10 invitations for interviews.
We rejected a reasonable number of decent candidates outright because they were looking for part-time work. If this is you, don’t feel dissuaded.
There were quite a few really bad applications (...as always): poor punctuation/capitalization, much too informal, not answering the questions, totally unrelated background, etc. Two suggestions: (1) If you’re the kind of person who is trying to application-max, make sure you actually fill in the application. A shitty application is actually worse than no application, and I don’t know why I have to say that. (2) If English is not your first language, run your answers through ChatGPT. GPT-3.5 is free. (Actually, this advice is for everyone).
Between 5 and 10 people expressed interest in an internship option. We’re going to think about this some more. If this includes you, and you didn’t mention it in your application, please reach out.
Quite a few people came from a data science / analytics background. Using ML techniques is actually pretty different from researching ML techniques, so for many of these people I’d recommend you work on some kind of project in interpretability or related areas to demonstrate that you’re well-suited to this kind of research.
Remember that job applications are always noisy. We almost certainly made mistakes, so don’t feel discouraged!