Taking a hiatus to learn more ML?

Question

I've been at a chaotic job for 3+ years and had a lot of stress before that. Very much looking forward to quitting soon and getting some rest. I also need space to learn and practice with no side tasks, boss, or other sources of stress.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.

XTXinverseXTY · Accepted Answer

This sounds like a bad idea. You are very smart to have asked before proceeding.
I 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.

mendeza · Answer

If you wanted to go back and do a PhD in ML, with your work experience you would be a great fit for the NSF Fellowship called CSGrad4US that supports engineers going back to research. https://www.nsf.gov/cise/CSGrad4US/ You have to be a US Citizen, and commit to a U.S. based university and in a CISE department (this is most CS departments). I am in the fellowship now and highly recommend it! Happy to answer any questions.

petercooper · Answer

Single with no children or family commitments? If you really feel the pull, go for it, otherwise you'll be thinking "what if?" in a few years.

stealthcat · Answer

Consider applying PhD program to some ML labs in Europe other than UK and France, they pay livable salaries like junior engineers. Better if in Swiss since the salaries are much higher.European ML labs generally have less prestige than US/China ML labs but they pay much more humane wages even for people with family.