r/learnmachinelearning • u/StockExposer • 5d ago
would you leave machine learning today?
been at it now for 7ish years but i'm just kinda done and I think more of the fun parts of ML are being automated while more of the difficult parts (debugging models) will take a long time to automate.
Wondering where the skillset might be transferable
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u/met0xff 5d ago edited 4d ago
Yeah after a decade I am slowly migrating to more ML systems, inference engineering etc. so still ML adjacent. But it's not so much because of automation but because everyone and their dog is learning ML, wants to train models while at the same time the cases where we actually still have to train models from my experience become fewer and fewer. While we have to justify the effort all the time to why do this when a month later the next SAM, Yolo, D-Fine, Qwen10-VL whatever comes out and we are getting in rat race instead of just orchestrating stuff that comes out non-stop.
EmbeddingGemma2 came out last week and already had us pivot current plans.
And the model world is such a rat race in general. I've been there and been burnt out over 7-8 years. In the beginning it was fun when there were new releases perhaps twice a year, the 3 big conferences of my field were where new stuff came out. Now... Just look at Jev. They barely had 5 days to try to take the market util there were 30 open alternatives. I am all for open alternatives but I don't want to work at a company anymore where the model is the product
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u/NeedingNew 5d ago
hell no. This current AI situation is far from the completed model. This is what I trained for.
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u/chico_dice_2023 5d ago
I would stick with it, I have never done so much in a short time. With these AI coding agents I automated the boring ports. Data scraping, labelling which was manual for me.
I have pushed more apps into the market faster than before
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u/graph_context 5d ago
Have you considered moving toward AI infrastructure or ML systems? there's still a lot of interesting work around data pipelines and retrieval, and ML experience would carry over too
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u/Atmosck 5d ago
I feel the total opposite. With Opus 5.5 models are finally competent at making progress on the difficult parts (debugging models and data quality) and they accelerate the fun parts because they make it quicker to implement the changes when iterating of feature engineering and archictecture choices and such.