[standfest]

Here are my 2¢: Leverage platforms that offer mock technical interviews (e.g., Pramp, Interviewing.io, probably there are others too). This approach lets you simulate the interview experience in a risk-free environment, getting you accustomed to the format and the pressure. It’s crucial to receive feedback, and these platforms pair you with industry professionals who can provide just that. This method is effective because it targets your interview skills directly, allows for rapid iteration based on feedback, and builds your confidence in a more controlled setting than actual interviews.

Aside from just technical skills, these mock interviews can help you articulate your thought process clearly, which is often as important as the solutions themselves in ML roles. Remember, it’s not just about getting the right answer, but also showing how you approach problems.

A side note based on a pattern I've observed so far: candidates who practice like this tend to perform better not just in technical assessments but also in explaining their past projects and teamwork experiences, which are equally critical parts of the interview process.

Hope this helps. Dive in, get that feedback, and refine your approach. Good luck!

[userabchn]

Before paying for mock interviews, it might be a good idea to first get practice with something like https://grow.google/certificates/interview-warmup/

[baka367]

There are also plenty of virtual groups around that offers p2p interviews (each side interviews another).

These might be better for initial warmup as the only cost is an extra hour of your time (but it also allows you to experience the interview from the interviewer's perspective).

[dsattt]

Isn't the feedback "get better at leetcode" and "talk while you're solving the problem"? These seem to be the universal reasons for rejection.