This paper presents a new control scheme using a sliding mode controller with a multilayer neural network for the robot manipulator operating under the sea which has large uncertainties such as the buoyancy and the added mass/moment of inertia. The multilayer neural network using the error back propagation loaming algorithm acts as a compensator of the conventional sliding mode controller to improve the control performance when the initial assumptions of uncertainty bounds are not valid. Computer simulation results show that the proposed control scheme gives an effective path way to cope with the unexpected large uncertainties in the underwater robot manipulator.