Recommender Systems, Software Architecture, Machine Learning, Testing, Backend.
do need to temporarily switch off a particular model and rely on our generic fallback recommendations rather than personalized ones. For example, when the model might be failing to scale because we’ve reached a scaling limit that needs to be increased by our cloud provider, simply rolling back