Techniques are described herein for generating and deploying network topologies to implement machine learning systems. A topology deployment system may receive data representing a logical model corresponding to a machine learning system, and may analyze the machine learning system to determine various components and attributes of the machine learning system to be deployed. Based on the components and attributes of the machine learning system, the topology deployment system may select target resources and determine constraints for the deployment of the machine learning system. A corresponding network topology may be generated and deployed across one or a combination of workload resource domains. The topology deployment system also may monitor and update the deployed network topology, based on performance metrics of the machine learning system and/or the current status of the system in a machine learning pipeline.