The Harsh Reality of Being an ML Researcher
Author(s): Boris Meinardus
Originally published on Towards AI.
What you need to expect when entering the field of ML research.
We all know that Machine Learning is the hottest thing to work on right now. And if you are a researcher, especially at a famous lab, start-up, or big tech company, you are literally at the frontier of developing the arguably biggest technology of mankind while earning a lot of money.
So, with this post, I definitely donβt want to talk down the ML researcher career, but I want to shed some light on what the harsh reality of being an ML researcher can look like and whether it is something for you.
For context, I have been an ML student researcher for the past 3 years, am collaborating with a researcher at Google DeepMind, have published a paper at a top conference, and have had 2 papers rejected.
Sigh⦠The last rejection was so stupid⦠I just have to explain it to you in a second.
Okay, letβs directly address the elephant in the room. How likely is it that you will become an ML researcher or even engineer who earns multiple 100k a year at a top company like OpenAI, Google, or Meta?
The short answer and harsh reality is: it is difficult. Very difficult. But not impossible.
Of course, for some, it is… Read the full blog for free on Medium.
Join thousands of data leaders on the AI newsletter. Join over 80,000 subscribers and keep up to date with the latest developments in AI. From research to projects and ideas. If you are building an AI startup, an AI-related product, or a service, we invite you to consider becoming aΒ sponsor.
Published via Towards AI