As interest in Artificial Intelligence (AI), and specifically Machine Learning (ML), grows and more engineers enter this popular field, the lack of de facto standards and frameworks for how work should be done is becoming more apparent. A new focus on optimizing the ML delivery pipeline is starting to gain momentum.