DeepRecSys provides an end-to-end infrastructure to study and optimize at-scale neural recommendation inference. The infrastructure is configurable across three main dimensions that represent different recommendation use cases: the load generator (query arrival patterns and size distributions), neural recommendation models, and underlying hardware platforms. DeepRecSys code available on GitHub.