I used to think this but after working in a large image processing team, I've come around to believe it's something management just rationalizes. In a lot of cases you _do_ need a big team with diverse research skills, otherwise you are deeply unable to pivot your own products and services for changes customer demands or adapt to situations when new models or competition elevate the minimal level of features that customers expect.
Building this stuff in a way that won't fall apart is really hard and you need a lot of people who are happy to be focused on the integration, deployment, and maintenance for sure. But you do also need a lot of people who are dedicated to the research, prototype, and model performance understanding side too, without trying to squeeze extra work out of them by trying to sell roles as a "hybrid" between integration and research.
Saying that "people don't give a shit about models" is vacuous, because ultimately the stack trace of what they do give a shit about will bottom out at issues with models that require a diverse team of experts to debug and solve.
I think companies are still stuck in a dreamworld right now where they want to believe that very junior engineers with tangential interest in machine learning are going to slot in at your standard $130k - $160k job offer (in major urban areas) and do just as adequate of a job as senior experts who might earn twice that.
But it doesn't work, and this type of penny pinching on the modeling side, rationalized by a false belief that you only need a tiny bit of research expenditure, I think is responsible for many start-ups failing and many projects being unwound in larger corporations.
This is just a silly point of view. What if someone is the victim of a huge restructuring, like a whole business unit or a whole team is let go?
What if someone gets bait-and-switched by a hiring manager. (This happens all the time with machine learning, for example... in which you are expected to display an astronomically better quality set of skills during hiring than what the job will actually afford you to use or develop once you start working).
What if someone has family problems, illness, etc. etc.?
What if someone experiences _multiple_ of these things within a given ~5 year period?
Truly, people complain all the time about job-hopping employees, but I don't see companies offering loyalty. People get randomly laid off for no fault of their own, sold on a vision of a job that never comes true, ripped off on their bonuses, or any number of other legitimate reasons to start looking for a new employer even after a short time.
Also, if you find yourself in a position where you are reading 300 resumes, you're clearly going about this all wrong, and with the attitude you describe about dismissing people without even the tiniest bit of critical thought put into it, I guess I shouldn't be surprised.
Building this stuff in a way that won't fall apart is really hard and you need a lot of people who are happy to be focused on the integration, deployment, and maintenance for sure. But you do also need a lot of people who are dedicated to the research, prototype, and model performance understanding side too, without trying to squeeze extra work out of them by trying to sell roles as a "hybrid" between integration and research.
Saying that "people don't give a shit about models" is vacuous, because ultimately the stack trace of what they do give a shit about will bottom out at issues with models that require a diverse team of experts to debug and solve.
I think companies are still stuck in a dreamworld right now where they want to believe that very junior engineers with tangential interest in machine learning are going to slot in at your standard $130k - $160k job offer (in major urban areas) and do just as adequate of a job as senior experts who might earn twice that.
But it doesn't work, and this type of penny pinching on the modeling side, rationalized by a false belief that you only need a tiny bit of research expenditure, I think is responsible for many start-ups failing and many projects being unwound in larger corporations.