ML methods people are talking about are mostly focused on prediction. Collinearity and confounding problems you describe will mess with those methods too, though it’ll be harder to recognize and diagnose. “feature importance” measures are generally as vague as the name implies. You’re doing it the right way, just keep working within that feedback loop of analyzing your data and improving your model.