I tried fine tuning gpt2 on 1000 examples on my M1, I think it was supposed to be 10 hours versus 30 minutes on a V100 on Gcloud. Inference was comparable. I think there is a way out by installing the right drivers, but honestly, what would be the point in that for someone who works in industry? I am not planning to run production code trained on a MBP, so might as well develop cloud first.

Are such jobs remote? I have worked previously in defense gigs where you are forced to work on computers that are air gapped. Seems to me that entire setup relies on being present physically.

I completely and totally sympathize with your issues with Leetcode. As someone who never enjoyed competitive programming, I think it is especially frustrating when I realize that it has become the default standard for hiring filters. The way I see it, choosing not to go down that route, seems to at this stage restrict one to very few companies.

In fact, there are way more companies who are finding it easier to set up an automatic hackerrank filter, which invariably involves a competitive programming question.

If you have a PhD, have relevant publications and you can apply for a research role, I suppose you can avoid it, at least at the Big companies.

But for Engineers, IDK, I know folks who are at the Principal/Staff level at G/FB/Amazon and even they have talked about having to undergo at least one Leetcode filter. And to be clear, I am talking about Machine Learning Engineers and not regular Software Engineers.

> I only allowed to navigate the docs but not StackOverflow or google search, I thought this should be about showing my abilities to understand the problem, the given data and process it as much as I can and get a good result fastly.

To me this is a sign that they are overfitting to a specific type of candidate. And simply put, their interview process is not robust. If the underlying intent is to find a candidate who has deeper insight into their tools, as opposed to what can be gained via copy pasting blocks of code, you can probe that super easily without this contrived approach. Ask them about how their tools work, contrasting one option versus the other and so on.

IMO, you shouldn't overfit to this experience either. I mean, if we allow for the possibility that an Engineer can be incompetent/crappy, we should allow for the possibility that a Manager (prepared to bet that the hiring manager probably has the same ~ 4 years or so of experience managing) can also be below average.

Yes, I think this is important to realize. Don't confuse the hardness (or easiness) of the interview with how challenging (or not) the actual job would be. After all, it is relatively cheap to make your interview process challenging. It is significantly harder to be an impactful company, hire the right kind of people etc.

> I rarely ever interview for big companies these days for the exact same reason.

I don't know of a big company (as in one of the elites) that would conduct an interview like what OP experienced. They might ask you leetcode questions, but no one is going to ask you to memorize pandas. Between the two, I will take understanding data structures over memorizing pandas any day.