The barriers to AI engineering are crumbling fast

I would interpret that as somebody working on ML algorithms and architectures, not somebody developing a product that uses some form of AI at runtime...

I haven't seen this sort of work called AI Developer yet, but I may have missed the trend shift. Isn't the convention for this still to use the title of Machine Learning Engineer (MLE)?

There is another thread here that seems to confirm it's me who has missed a trend shift. I didn't know this term had a special meaning. I just followed the thought that an x-developer is somebody developing x.

I work on such a team, and we don't refer to ourselves as "AI engineers". We're devs working on developing deep learning systems (but not genAI).

correct - but "developing a product that uses some form of AI at runtime" is a job that people do and the community has consolidated around "AI engineer" as shorthand https://www.latent.space/p/ai-engineer

i argue that its useful to have these shorthands to quickly understand what people do. its not so nice to just be default suspicious at a perhaps lower-technical-difficulty job that nevertheless a lot of comapnies want and a lot of people do

Difficulty ≠ Value

But we think it is, due to our learned industrious—which is the opposite of learned helplessness. We associate difficulty with reward. And we feel discomfort when really valuable things become very easy. Strange times.

> devs working on developing deep learning systems (but not genAI)

Catchy job title.

I work on such a team too. I don't care what you call me - pay me

They use "AI" like they use "Python" in "Python developer" or "Web" in "Web developer".

Why is it lower difficulty? If didn't get that impression from the article

My job title is "software engineer".