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The Machine Learning Job Market

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Re: The Machine Learning Job Market

#11
post #9
post #4

A lot of opinions and unverifiable statements (this and this company is X years ahead of everyone), and the whole piece is essentially about one person's job market. Skip

I’m interested in understanding the ML job market for traditional software developers. Does the opportunity exist to transition into any particular ML roles then grow from there?

I've been seeing a lot of Data Engineering/Platform roles that support ML without requiring past ML experience. How much future lateral movement would be available to you will vary widely, but this would be a fairly easy inroad.

Re: The Machine Learning Job Market

#12
I was expecting something along the lines of how AI/ML was considered a sexy career path, but there are very few jobs available and high competition for those jobs. So, as a result, you end up with the only available jobs as data engineering/ML ops/backend that supports ML teams. I am happy for this author and their success, but they clearly are not representative of the majority of the people in the ML job market.

Re: The Machine Learning Job Market

#15

You forgot to write that crypto startups compete with publicly traded FAANG on compensation on both cash and non-cash compensation, and there is no liquidity issue whatsoever on the non-cash they pay you with. Vesting schedules are more competitive than FAANG. And the publicly traded crypto companies compete with FAANG on compensation too. Non-crypto startups are the only ones sitting in the doldrums left out to dry…

This doesn't sound quite right to me; Coinbase pays well, but looking at levels.fyi it's not FAANG money; is there someone else you have in mind?

Would love to hear more about the startups; I tend to turn down such opportunities far before we talk non-cash comp.

Re: The Machine Learning Job Market

#17

> The most important deciding factor for me was whether the company has some kind of technological edge years ahead of its competitors. A friend on Google’s logging team tells me he’s not interested in smaller companies because they are so technologically far behind Google’s planetary-scale infra that they haven’t even begun to fathom the problems that Google is solving now, much less finish solving the problems that…

On the other hand, there’s a lot of real problems that real people actually deal with that just need a logistic regression to save million bucks here and there. I like that space more.

Re: The Machine Learning Job Market

#19
post #12

I was expecting something along the lines of how AI/ML was considered a sexy career path, but there are very few jobs available and high competition for those jobs. So, as a result, you end up with the only available jobs as data engineering/ML ops/backend that supports ML teams. I am happy for this author and their success, but they clearly are not representative of the majority of the people in the ML job market.

I think I have a decent CV, with quite a bit of experience for a master's student. I have been searching for a job in MLE, for a bit now with very little to show for it, as I am either getting no responses, or responses claiming that they are looking for more experienced people, and particularly those that had experience with a particular stack.

In all honesty, after 6 years of studying, with 4 of those years studying ML, to be told that I lack experience with some particular stack as the ~~excuse~~ reason for rejection feels like a slap in the face.

And all that ignoring everything that expects 3+ years experience for entry level positions.

Re: The Machine Learning Job Market

#20

> The most important deciding factor for me was whether the company has some kind of technological edge years ahead of its competitors. A friend on Google’s logging team tells me he’s not interested in smaller companies because they are so technologically far behind Google’s planetary-scale infra that they haven’t even begun to fathom the problems that Google is solving now, much less finish solving the problems that…

You are talking about 2 commodities that can easily be upgraded: logging and UX. Hell, I wouldn’t even waste too many precious resources on improving those things past a point.

Google has massive data and scaling advantages that can never be duplicated or fixed by smaller companies.

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