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How I Became a Machine Learning Practitioner

blog.gregbrockman.com

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Re: How I Became a Machine Learning Practitioner

#41

Post by bitL »

nilkn wrote: post #38
bitL wrote: post #36

Earlier quoted context omitted.

ML engineer is a super boring job content-wise and has insane outside pressure. It's about building data pipelines, the ugly grunt work. ML/Data Scientist is the interesting job. Usually Data Scientists view ML Engineers as replaceable drones that don't understand anything interesting and do the boring part of the job for 2-3x less than they do. The only advantage of ML Engineers is that AutoML is unlikely going to r…

I might disagree on this. The software engineering behind production machine learning systems can be quite interesting and nontrivial. It really depends on the scope of the challenges being faced. If you have thousands of models that need to be served in production and continually retrained and monitored, that becomes a pretty sophisticated problem space to work in.

Yes, however most ML engineers don't get to work at Jeff Dean's level to actually do such interesting work. There are very few companies willing to write their own Horovod or distributed PyTorch.

Re: How I Became a Machine Learning Practitioner

#42

Post by rolltiide »

TrackerFF wrote: post #30

I think it's doable if you're at the right place and have enough opportunities around you, and something to show for. I feel that companies and startups around tech hubs are more willing to give someone a chance, and look through the formality, if you manage to convince / impress them. Where I live, far away from tech, it's almost impossible to land a job in ML / AI / DS unless you have a (minimum) Masters degree in…

Your observation is correct. No degrees are needed there is a lot of stuff to build.

Re: How I Became a Machine Learning Practitioner

#43

Post by badpun »

jorblumesea wrote: post #13

Does anyone not want to become a ML engineer? Is this the future, and will we even have a choice or else be out of a job?

I got an offer to do ML on video data recently, but turned it down to do some non-ML software eng. instead, for double the money. The ML work would be way cooler, but it would at a startup (=stressful) and double the money means half the time to reach FIRE.

The caveat is that I've worked on ML in the past and I think that the work is maybe less intellectual than software engineering - with complex enough models they become impossible to understand and you start to just try out ideas based on random intuitions. The thing I mostly like about it is the ability to use math and more independent style of work - no scrum, less need for cooperation with other team members etc..

Re: How I Became a Machine Learning Practitioner

#44

Post by carlmr »

rhacker wrote: post #23
klipt wrote: post #18

Earlier quoted context omitted.

There's plenty of non ML software engineering to be done. Anecdotally a large proportion of interns want an "ML project", but only a small percentage of teams looking for interns are offering one. Too many people going into ML could skew the supply/demand into making it a worse job option (more work, less pay), like game programming or academia.

The question is this: 10 years from now when the top job requirements list ML - are you going to be ready or out of the game?

Alternatively the market is flooded with ML people and the value of ML on your CV is 0.

Re: How I Became a Machine Learning Practitioner

#46

Post by knbknb »

gdb wrote: post #4
copperx wrote: post #3

Earlier quoted context omitted.

Studying Math at Harvard/MIT certainly puts you in a different category than the average software engineer. And if ML was still challenging to Greg, it is honestly a bit discouraging.

(I wrote the post.) If it's helpful, I dropped out of both schools — the vast majority of my knowledge is self taught!

How often do you go "back to basics" (read introductory book chapters, or classic papers, etc)?

Re: How I Became a Machine Learning Practitioner

#48

Post by anon44 »

bitL wrote: post #36
jorblumesea wrote: post #13

Does anyone not want to become a ML engineer? Is this the future, and will we even have a choice or else be out of a job?

ML engineer is a super boring job content-wise and has insane outside pressure. It's about building data pipelines, the ugly grunt work. ML/Data Scientist is the interesting job. Usually Data Scientists view ML Engineers as replaceable drones that don't understand anything interesting and do the boring part of the job for 2-3x less than they do. The only advantage of ML Engineers is that AutoML is unlikely going to r…

the vast majority of ML/data scientist positions are actually similar to the hypothetical ML engineer position you described.

Re: How I Became a Machine Learning Practitioner

#49

Post by strikelaserclaw »

mychael wrote: post #22

Congrats on your cool life, your ivy league education, your CTO role at OpenAI and all the access that provides. You've done it! Also thanks for telling us how you became a practitioner. It's definitely relatable and not a humble brag at all.

Jealousy is unbecoming. I had no idea who this guy was and i found the article nice to read. It is a story about a guy who feels out of his depth in a highly technical domain but instead of giving up, he devotes time to it and comes out the other end much more competent. The internet provides everyone with world class experts to help you if you are stuck on something, most people don't have the will to help themselves.

Re: How I Became a Machine Learning Practitioner

#50

Post by thundergolfer »

threeseed wrote: post #32
jorblumesea wrote: post #13

Does anyone not want to become a ML engineer? Is this the future, and will we even have a choice or else be out of a job?

I started in ML about 7 years ago so well before the hype and back then very few people wanted to be ML engineers. What's happening at least in Australia now is that contract rates (a good indicator of the supply/demand ratio) has halved for ML engineers. Which means (a) a lot of people want to be ML engineers and (b) there aren't that many jobs for them.

Just to be sure I understand correctly, you’re saying that money has halved for ML engineers because plenty of people are getting into ML and are willing to take much less money? You said they “want to be” ML engineers which implies they aren’t really and thus aren’t worth ‘full-rate’
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