These neural approaches aim to obviate the need for any feature engineering and instead focus on developing a neural architecture that learns the representations and the ranking.
while it is possible to view a purely neural approach as an alternative to machine learning involving domain knowledge in the form of handcrafted features, there is no reason why the two approaches cannot be applied in tandem.