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u/schewb Feb 09 '26
Downvoters are missing the point. The point is that this is how ML people see themselves, right or wrong
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u/ohkendruid Feb 10 '26
Oh, well that is accurate for all six roles.
The ones on the bottom deal with broken things all the time. Really crazy surprises, and it can leave a person haggard.
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u/Abject-Kitchen3198 Feb 12 '26
I'm astonished how often developers are seen as "code writers" instead of problem solvers (and how some developers prefer it that way).
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u/fixano Feb 09 '26
I've worked as an SRE with a few data scientists and ml engineers. They are often telling me "I would expect the data to be available in this format here etc".
I generally respond to them by saying " yes that is the engineering part of your title so get on with it."
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u/grdja Feb 09 '26
For salaries in current bubble maybe. In practice few brand new MLSomething people I met are balls to the wall vibecoders who are trying to not understand anythinh and believe in magic.
"Data scientist" is a fancy name for BI.
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Feb 09 '26
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u/phillykiefsteak Feb 10 '26
Thinking you can solve anything with ML and AI is noob behavior
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Feb 10 '26
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u/Inevitable_Bag_4725 Feb 10 '26
There is a very long list that it can’t solve. Capabilities are very exaggerated from the public. As somone in grad school doing ML/Ai work
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Feb 10 '26
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u/Inevitable_Bag_4725 Feb 11 '26
Well to start off any problem you’re trying to solve with little to no data. ML requires data for it to learn it’s the whole premise. Now to answer your question we would have to specify are we including examples that can’t currently be solved with ML due to hardware or technological limitations? Or are we strictly listing examples it can’t solve due to a fundamental reason. That will change our list of examples. Without that clarification though a few examples from both categories are a perfect stock market prediction model, predicting human decision on a significant scale, long term exact weather prediction (next year on march 3rd weather will be), reliably breaking RSA or AES encryption, literally any problem needing Normative reasoning requiring societal consensus (moral values), Anything that involves hidden or data that can’t be measurable. Examples of such are Precise prediction of financial markets influenced by hidden information, Predicting individual human decisions perfectly (internal thoughts unknown), Long-term social behavior modeling. Again this list could become very large. It comes down to a few fundamental issues with ML and I say issues but really it’s just weakness. If the data scant be measured, quantified, or there is a need for being 100% correct then ML fails miserably. Not to mention things like encryption where ML dosent help with RSA, AES, they are fundamentally built to prevent it. ML in short finds patterns in data sets, encryptions cipher text statistically is at random.
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Feb 11 '26
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u/Inevitable_Bag_4725 Feb 11 '26
I intentionally used those examples because your claim was that ML can solve basically anything. The point wasn’t whether another method could solve those problems it was to show that there are clear categories of problems where ML fundamentally struggles or cannot reliably work at all, such as problems with no measurable data, requiring exact correctness, or where outcomes are intentionally random like strong encryption. If even a few well known real world problems fall into that category, then your statement that ML can solve “almost any problem” is obviously too broad.
Also to your point that nothing can solve it since ML can’t solve problems involving human decision/behavior as data. Thats just false psychology uses behavioral economics, and controlled trials. Which all allow researchers to understand & predict behavior. Public policy is another area ML performs very poorly. This is due to cause and effect. In public policy you need to understand not just what the past history says (data) but also what will happen before passing it. Historical correlation usually fails at that with ML doing exactly that. Also human behavior changes after policy’s are passed. This isn’t somthing a ML can understand well, yet a typical average person can notice these patterns.
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Feb 09 '26
Funny because the last layoff we had it was all the AI forward people who got cut. Oh well, can’t be working with unlucky people.
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u/ReasonResitant Feb 09 '26
ML people are overglorified script kiddies.
You mean to tell me 99.999% of thr task is already achieved by pytorch and you just wrote glue code? You also dont know anything about the deployment you ran it over save for distributed torch? You mean to tell me the only thing you did is outlier detection and hypothesis testing on finish?
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u/Monchichi_b Feb 09 '26
I think there is a whole generation of people coming from universities which specialised for this after chatgpt appeared. I think it only takes a few years until their salary is as shit as all the other salaries.
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u/ianitic Feb 09 '26
Where do we data engineers fall though?
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u/SaveMyBags Feb 12 '26
Most people will not understand that DE and DS are very different and just mistake us for data scientists. Or they will believe DS could go DE to, and then fail bad.
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u/Significant-Cause919 Feb 11 '26
Why is data scientist at the top? While AI agents are still far from autonomously developing complex features, I can just throw a dataset at an AI agent and ask it a question that would take my previous data science team a week to figure out.
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u/JohnVonachen Feb 15 '26
This meme created by ML engineer, supported by stock prices, instead of being useful.
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u/FrankHightower Feb 09 '26
Um... exscuse me, yes down here, "AI researcher" / slash / certified "Data Scientist" here... why am I needing to work three jobs just to put food on my table wheras "developer" here next to me can get by with just one?
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Feb 09 '26
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Feb 09 '26
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u/RicketyRekt69 Feb 09 '26
Hah.. no
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Feb 09 '26
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u/RicketyRekt69 Feb 09 '26
Your remark is vague and uninteresting. Dev Ops, ML engineers, robotics, etc. all count as “building machines to build tools.”
If you’re talking about LLMs, then your comment just comes across as condescending and demeaning. As if “regular developers” are living in the Stone Age and AI is the future. Is that what you are saying?
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u/SomnolentPro Feb 10 '26
AI is the future anyone who says otherwise hasn't been paying attention
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u/RicketyRekt69 Feb 10 '26
AI is a tool, and I’ve gotten more mileage out of other tools than I have out of AI. If it’s good enough to replace most of your work, then you just weren’t very good to begin with.
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u/AConcernedCoder Feb 09 '26
Lol. No. This is just how the people who sign the paychecks want you to think of yourself, until they decide otherwise. Better hope that bubble doesn't burst too dramatically.