1. A computer-implemented process for recommending tasks to workers, comprising: using a computer to perform process actions for: receiving specifications for one or more tasks having a plurality of task contexts from one or more task publishers; receiving a separate machine-learned predictive worker model for each of a plurality of workers in a worker pool; receiving one or more current contexts for each of the workers in the worker pool; and evaluating the tasks, the task contexts, the worker models, and the current contexts to construct optimized bundles of one or more tasks that are then recommended to particular workers from the worker pool, such that a predicted task completion rate over available tasks is maximized by the bundle construction and task recommendation.