Ask HN: Taking a hiatus to learn more ML?
In my head, the ideal next few months would be spent in a low-CoL European country with a laptop and my 20k in savings, learning at my own pace and practicing the implementation of ML ideas. Then searching for jobs that match what I want, mostly in the US. And sticking to a couple hours of work per day, or whatever amount doesn't feel bad for me.
I've got experience implementing computer vision models, building inference/training pipelines, doing devops, programming in Python and C++, and a few other things. My goal is ML research or engineering on large pipelines. Current job doesn't leave me the energy to learn a lot by myself.
Does this sound like an extremely bad idea, given what everyone on here is saying about the tech job market, and that I'm not very experienced? I would appreciate any kind of advice, from people who have taken a hiatus, or recruited someone after one, or who know more about the ML job market and what employers are looking for.
16 comments
[ 0.21 ms ] story [ 116 ms ] threadI work as an MLE at a growth-stage startup with ~20 MLE/MLS folks. I was unemployed for 6 months before getting this job with 4YOE as an MLE and DS. There are too many qualified candidates.
ML research is out of the question. Most of the people who get to do ML research have PhDs, if not the only people. This seems like a racket but it exists for a good reason. It's hard for employers to evaluate the quality of MLS candidates through an interview, they don't know what to ask him. And if they've hired one, it's hard to know whether to fire him, things rarely pan out in research. The whole time, they have to trust this dweeb to run experiments burning tons of $$$ in compute! Employers are wise to be risk-averse, and to defer to costly social signals.
If you're going to take yourself off the job market for a long time, you had better at least get some kind of legible social signal out of it, like a master's degree. Almost all of the MLEs I work with have at least an MS in a relevant subject, the rest have PhDs.
Now, if I were to look for ML engineering positions after that hiatus, would that change the answer? I already have some experience in that.
(I should have been clearer that I’m not expecting a research scientist job right away, I’d like to upskill and then take a job I’m qualified for, and try the PhD route later.)
An MS probably doesn't have that much more of a causal effect on your ability to do good ML work, as opposed to an equivalent amount of diligent self-directed study, which is what I assumed you were considering. But *the hiring market is dumb*, hence my spiel about social signals.
So now I'm less confident about the hiatus. I still don't think it's a good idea, but certainly not as terrible, and I think the HN consensus would be slightly in favor of it.
If you haven't already, consider posting this question to teamblind. Yes it's an incredibly toxic community, but it attracts people ruthlessly interested in maximizing their compensation. HN is biased towards entrepreneurship.
Thanks for the advice! I’ll think hard about whether I really want to do this.
European ML labs generally have less prestige than US/China ML labs but they pay much more humane wages even for people with family.
Point taken about selection though! I’m thinking I could network with academics while working on implementing papers, etc.
Do you think the selection situation is different for foreigners? Do you know if the same is true about European schools? The 3-year average for PhDs in Europe really looks more attractive to me.
Also would really appreciate if you could tell me more about how these programs select people who aren’t 4.0 students from a top school with famous recommendations. Is practice important, should you know a lot about current SOtA, do you need to show math proficiency?