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Ask HN: Machine learning engineers, what do you do at work?

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Re: Ask HN: Machine learning engineers, what do you do at work?

#151

Post by aswegs8 »

hamasho wrote: post #82
schmookeeg wrote: post #66

Getting my models dunked on by people who can't open MS Outlook more than 3 tries out of 5, however, have a remarkable depth and insight into their chosen domain of expertise. It's rather humbling. Collaborating with nontechnical people is oddly my favorite part of doing MLE work right now. It wasn't the case when I did basic web/db stuff. They see me as a magician. I see them as voodoo priests and priestesses. When…

I worked on a project to analyze endoscope videos to find diseases. I examined a lot of images and videos annotated with symptoms of various diseases labeled by assistants and doctors. Most of them are really obvious, but others are almost impossible to detect. In rare cases, despite my best efforts, I couldn't see any difference between the spot labeled as a symptom of cancer and the surrounding area. There's no a-h…

Mind sharing how to get a foot into the field? I've got a good amount of domain knowledge from my studies in life science and rather meager experience from learning to code on my own for a few years. It seems like I cant compete with CS majors and gotta find a way to leverage my domain knowledge.

Re: Ask HN: Machine learning engineers, what do you do at work?

#152

Post by xtagon »

Xenoamorphous wrote: post #143

I’m a regular software dev but I’ve had to do ML stuff by necessity. I wonder how “real” ML people deal with the stochastic/gradient results and people’s expectations. If I do ordinary software work the thing either works or it doesn’t, and if it doesn’t I can explain why and hopefully fix it. Now with ML I get asked “why did this text classifier not classify this text correctly?” and all I can say is “it was 0.004 p…

Not all ML is built on neural nets. Genetic programming and symbolic regression is fun because the resulting model is just code, and software devs know how to read code.

Re: Ask HN: Machine learning engineers, what do you do at work?

#153

Post by nchfgsj1 »

xtagon wrote: post #152
Xenoamorphous wrote: post #143

I’m a regular software dev but I’ve had to do ML stuff by necessity. I wonder how “real” ML people deal with the stochastic/gradient results and people’s expectations. If I do ordinary software work the thing either works or it doesn’t, and if it doesn’t I can explain why and hopefully fix it. Now with ML I get asked “why did this text classifier not classify this text correctly?” and all I can say is “it was 0.004 p…

Not all ML is built on neural nets. Genetic programming and symbolic regression is fun because the resulting model is just code, and software devs know how to read code.

Genetic programming however isn’t machine learning, but instead it’s an AI algorithm. An extremely interesting one as well! It was fun to have my eyes opened after being taught genetic algorithms, to then be brought into genetic programming

Re: Ask HN: Machine learning engineers, what do you do at work?

#154

Post by kobalsky »

globular-toast wrote: post #107
davedx wrote: post #5

pip install pytorch Environment broken Spend 4 hours fixing python environment pip install Pillow Something something incorrect cpu architecture for your Macbook Spend another 4 hours reinstalling everything from scratch after nuking every single mention of python pip install … oh time to go home!

You could learn how to use Python. Just spend one of those 4 hours actually learning. Imagine just getting into a car and pressing controls until something happened. This wouldn't be allowed to happen in any other industry.

I've been programming with python for decades and the problem they are describing says more about the disastrous state of python's package management and the insane backwards compatibility stance python devs have.

Half of the problems I've helped some people solve stem from python devs insisting on shuffling std libraries around between minor versions.

Some libraries have a compatibility grid with different python minor versions, because how often they break things.

Re: Ask HN: Machine learning engineers, what do you do at work?

#155

Post by htrp »

nomilk wrote: post #144
schmookeeg wrote: post #66

Getting my models dunked on by people who can't open MS Outlook more than 3 tries out of 5, however, have a remarkable depth and insight into their chosen domain of expertise. It's rather humbling. Collaborating with nontechnical people is oddly my favorite part of doing MLE work right now. It wasn't the case when I did basic web/db stuff. They see me as a magician. I see them as voodoo priests and priestesses. When…

The Dead Internet Theory says most activity on the internet is by bots [1]. The Dead Privacy Theory says approximately all private data is not private; but rather is accessible on whim by any data scientist, SWE, analyst, or db admin with access to the database. [1] https://en.wikipedia.org/wiki/Dead_Internet_theory

> The Dead Privacy Theory says approximately all private data is not private; but rather is accessible on whim by any data scientist, SWE, analyst, or db admin with access to the database.

I like this so much I'm definitely stealing it!

Re: Ask HN: Machine learning engineers, what do you do at work?

#158

Post by rurban »

Highly paid cleaning lady. With dirty data you get no proper results. BTW: perl is much better than python on this.

Highly paid motherboard troubleshooter, because those all those H100's really get hot, even with watercooling, and we have no dedicated HW guy.

Fighting misbehaving third-party deps, as everyone else.

Re: Ask HN: Machine learning engineers, what do you do at work?

#159

Post by fbdab103 »

ninkendo wrote: post #124
davedx wrote: post #5

pip install pytorch Environment broken Spend 4 hours fixing python environment pip install Pillow Something something incorrect cpu architecture for your Macbook Spend another 4 hours reinstalling everything from scratch after nuking every single mention of python pip install … oh time to go home!

I count at least a half dozen “just use X” replies to this comment, for at least a half dozen values of X, where X is some wrapper on top of pip or a replacement for pip or some virtual environment or some alternative to a virtual environment etc etc etc. Why is python dependency management so cancerously bad? Why are there so many “solutions” to this problem that seem to be out of date as soon as they exist? Are pyt…

I think it is worth separating the Python ML ecosystem from the rest. While traditional Python environment management has many sore points, it is usually not terrible (though there are many gotchas still-to-this-day-problems that should have been corrected long ago).

The ML system is a whole another stack of problems. The elephant in the room is Nvidia who is not known for playing well with others. Aside from that, the state of the art in ML is churning rapidly as new improvements are identified.

Re: Ask HN: Machine learning engineers, what do you do at work?

#160

Post by htrp »

schmookeeg wrote: post #66

Getting my models dunked on by people who can't open MS Outlook more than 3 tries out of 5, however, have a remarkable depth and insight into their chosen domain of expertise. It's rather humbling. Collaborating with nontechnical people is oddly my favorite part of doing MLE work right now. It wasn't the case when I did basic web/db stuff. They see me as a magician. I see them as voodoo priests and priestesses. When…

>Getting my models dunked on by people who can't open MS Outlook more than 3 tries out of 5, however, have a remarkable depth and insight into their chosen domain of expertise. It's rather humbling.

The people who have lasted in those roles have built up a large degree of intuition on how their domains work (or they would've done something else).

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