Domestic ultrasonic flow meters with an intrusive two-stand configuration present a complex flow behaviour due to their unique geometry, which offers an interesting case to evaluate optimisation methods in wall-bounded flows. In this study, the design and analysis of computer models together with shape optimisation by solving the adjoint equations are utilised to predict the turbulent flow and to perform robust geometry optimisation of the flow meter. The optimisation is accomplished by surrogate modelling based on Kriging, Latin hypercube sampling, and Bayesian strategies. A novel function to quantify flow meter measurement uncertainty is defined and evaluated together with pressure drop in order to define the multi-objective optimisation problem. The optimisation Pareto front is shown and compared numerically and experimentally against pressure drop and laser Doppler velocimetry experiments, displaying performance gains and geometrical changes in the 3D space. Subsequently, these designs are further improved by computational fluid mechanics and the discrete adjoint method. The applied methodology provides a robust and efficient framework to evaluate design changes and improve ultrasonic flow meters or any internal-flow problem with similar features.