That's the advantage of deep learning over traditional ML: if you've got enough data, you don't need domain knowledge or hyperparameter tuning, just throw a large enough universal approximator at it. The challenge lies in generating good enough artificial data for domains without enough data, and getting deep models to perform competitively with simpler models.