I do think it's true, and likely the majority view too. The saying has many, many alternatives (for quantitative finance, it's "you can teach a math PhD finance but you can't teach a finance PhD math [at the same level that a math PhD is at]") in different studies.
I think it just boils down to knowing the fundamentals or not, and arguably a person who only studied ML will lack a wide range of tools in their toolkit to be able to tackle tangential problems that an engineer could (whereas the engineer already has the tools to build up their ML toolkit). In my anecdotal experience with teaching, knowing how to learn is heavily correlated with how general (as opposed to focused) the field the person is in.
I think it just boils down to knowing the fundamentals or not, and arguably a person who only studied ML will lack a wide range of tools in their toolkit to be able to tackle tangential problems that an engineer could (whereas the engineer already has the tools to build up their ML toolkit). In my anecdotal experience with teaching, knowing how to learn is heavily correlated with how general (as opposed to focused) the field the person is in.