We provide an overview of the tools available to data scientists using R for Spark and TensorFlow, then discuss the latest developments at the intersections of these ecosystems. We organize the conversation around a diverse selection of use cases, such as ad hoc analysis on distributed datasets, building machine learning models for low latency scoring, and developing deep learning models for research, and demonstrate sample workflows. Various open source R packages will be featured, including the sparklyr, keras, and tensorflow projects.