Description: Recent shifts to a remote economy have accelerated online commerce activities and the need to access remote information repositories. Information discovery is enabled through Search and Recommendations, but users expect Google-like quality results. In this talk, we discuss several ML strategies and design considerations around collecting and using signal data to train ranking algorithms and Collaborative Filtering recommenders as a component of a larger information portal. Recent progress in NLP and deep learning have ushered in a new wave of search methodologies, primarily vector based search which is distinctly different to lexical based search engines. We discuss how your businesses can leverage these advancements to drive a better user experience around information retrieval.