"I’ve seen repeatedly that it’s much harder for a ML PhD to learn chemistry than for a chemist to learn ML. (This may be survivorship bias; the only chemists I encounter are those that have successfully learned ML, whereas I see ML researchers attempt and fail to learn chemistry all the time.)"

This is something that rings really true to me. I work in imaging and it's just very clear that there are groups of people in ML that don't want to learn how things actually work and just want to throw a model at it (this is a generalization obviously, but it's more often than not the case). It only gets you 80% there, which is fine usually, but not fine when the details are make or break for a company. Unfortunately that last 20% requires understanding of the domain and people just don't like digging into a topic to actually understanding things.