ML in practice (from my xp) is mostly getting and cleaning data. As far as training, testing, and deploying a model, to an engineer it's just more algorithms.
While some algorithms may have more explainability than others, the engineer cares if they solve the business problem at hand.
While some algorithms may have more explainability than others, the engineer cares if they solve the business problem at hand.