
How I Became a Machine Learning Practitioner - sama
https://blog.gregbrockman.com/how-i-became-a-machine-learning-practitioner
======
TrackerFF
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 something relevant.
Preferably a Ph.D and solid experience to show for - I know because I work in
the field, and lots of F500 dinosaurs are just now waking up. But are also
unfortunately clinging to their old ways of hiring people.

Schools all over are also picking up slack, starting to offer specialized
graduate degrees in those domains. When I got my degree in ML, it was a sub-
field at my schools engineering department, mixed up with signal processing
and control theory groups.

When first trying to get a job, the main problem was to explain what I
actually could bring and do, and a lot of the recruiters or managers had no
idea what Machine Learning was. Then you said "It's basically Artificial
Intelligence" and, and they were instantly wooed.

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

------
minimaxir
Given that Greg Brockman was the CTO of Stripe before OpenAI, that's a order
of magnitude more technically/CS capable than the typical reader who might be
looking into ML.

~~~
copperx
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.

~~~
gdb
(I wrote the post.)

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

~~~
jcims
>I learn best when I have something specific in mind to build.

This is so incredibly important for me and, based on my conversations, many
others as well.

The other thing I struggle with is the feeling that many of the problems I
wish to solve are likely also solvable with simpler statistical methods and
that I'm just being a poser by trying to pound them home with the ML hammer.

------
jorblumesea
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?

~~~
bitL
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 replace some dirty work but
might endanger outdated Data Scientists.

~~~
nilkn
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.

~~~
bitL
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.

------
mychael
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.

~~~
ilyasut
Comments like this are what make HN great and are not at all toxic!

------
croh
Indeed inspirational article.

