Machine learning has shown remarkable capabilities in tasks related to machine vision, natural language processing, and general prediction problems. However in the healthcare setting, building tools that will translate into the clinical setting in a way that improves patient outcomes and helps the healthcare workflow has been limited by confounding factors, domain shifts, and regulatory challenges. We believe that the deployment of machine learning in the hospital setting will require technical expertise to play a collaborative rather than a leading role in the development pipeline.