For an antibody to make an effective therapeutic, it must both bind to its target and be free from developability issues, such as aggregation, poly-specificity, and poor expression levels. By either limiting our search space to developable antibodies, or building methods to engineer out developability issues, the success rate of therapeutic antibodies can be increased. My DPhil aims to tackle both problems using generative machine learning methods.