Systems and methods are provided for search result optimization using machine learning models. A search system uses machine learning models generate a target vector based on query features of a search query and a set of listing vectors based on listing features of listings identified as part of the search query. The target vector represents an estimated optimal listing for the search query and each listing vector represents a corresponding listing identified as part of the search query. The search system determines distances (e.g., Euclidian distance) between each listing vector and the target vector. The determined distances indicate how similar each listing is to the estimated optimal listing for the search query. The search system ranks the listings based on the distances such that listings that are similar to the estimated optimal listing are ranked higher than listing that are not similar to the estimated optimal listing.