[santaclaus]

> If you're doing _groundbreaking_ research

I think research is the key word here. If you are developing fundamentally new ML techniques (like the folks at Google), you'll probably need some serious technical chops.

> Usually it is a rinse-test-repeat kind of job. It needs people with patience and who can interpret data and who can be comfortable with uncertainty and then can make their bosses comfortable with uncertainty on timelines.

That sounds less like research and more like applying established tools (Tensor Flow or Keras or whatever).

[hobofan]

> If you are developing fundamentally new ML techniques (like the folks at Google)

Nope, still no superstars needed. The most technically challenging thing they've built is probably is what they are doing with the TPUs, but even there you "just" need people expierienced in the right fields. Most groundbraking research stuff these days is mostly on the mathematical side, not the implementation.

[maxxxxx]

"That sounds less like research and more like applying established tools (Tensor Flow or Keras or whatever). "

This is what most AI, ML and data science people do from my experience. It's really not that groundbreaking.