Artificial intelligence and machine learning have become important components of the computational toolbox that can be used to advance chemical research and discovery. In this talk, I will describe our recent work in analytical chemistry, specifically using tandem mass spectrometry data for structure elucidation of unknown small molecule metabolites. A pervasive theme of our research is the use of domain expertise to inform modeling, from formulating chemistry challenges as statistical learning problems to designing new neural network architectures uniquely suited to chemistry data.