A network system comprising: a computing system disposed within a remote network management platform and communicatively coupled to a scheduler device and a plurality of trainer devices disposed within the remote network management platform, wherein each trainer device of the plurality of trainer devices is configured to execute one or more machine learning, ML, trainer processes, and wherein the computing system is configured to: receive information indicating (i) training data that is associated with the computing system and that is to be used as basis for generating an ML model and (ii) a target variable to be predicted using the ML model, wherein the information is received from a client device of a managed network, and wherein the remote network management platform remotely manages the managed network; based on the received information, transmit an ML training request to the scheduler device, wherein the scheduler device assigns the ML training request to a particular trainer device of the plurality of trainer devices to execute a particular ML trainer process of the one or more ML trainer processes, wherein the scheduler device provides an instance identifier of a particular computational instance to the particular trainer device, wherein the instance identifier enables direct communication between the particular trainer device and the particular computational instance; receive a secure identifier from the particular trainer device; verify that the particular trainer device is permitted to obtain the training data; in response to verifying that the particular trainer device is permitted to obtain the training data, provide the training data to the particular trainer device executing the particular ML trainer process that is serving the ML training request; receive, from the particular trainer device, the ML model that is generated based on the provided training data and according to the particular ML trainer process; predict the target variable using the ML model; and transmit, to the client device, information indicating the target variable. receive information indicating (i) training data that is associated with the computing system and that is to be used as basis for generating an ML model and (ii) a target variable to be predicted using the ML model, wherein the information is received from a client device of a managed network, and wherein the remote network management platform remotely manages the managed network; based on the received information, transmit an ML training request to the scheduler device, wherein the scheduler device assigns the ML training request to a particular trainer device of the plurality of trainer devices to execute a particular ML trainer process of the one or more ML trainer processes, wherein the scheduler device provides an instance identifier of a particular computational instance to the particular trainer device, wherein the instance identifier enables direct communication between the particular trainer device and the particular computational instance; receive a secure identifier from the particular trainer device; verify that the particular trainer device is permitted to obtain the training data; in response to verifying that the particular trainer device is permitted to obtain the training data, provide the training data to the particular trainer device executing the particular ML trainer process that is serving the ML training request; receive, from the particular trainer device, the ML model that is generated based on the provided training data and according to the particular ML trainer process; predict the target variable using the ML model; and transmit, to the client device, information indicating the target variable.