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Thermoset polymer composite structures are heavily used in the aerospace, defense, transport, and energy sectors due to their lightweight and high-performance behavior. Thermoset polymer resins require external heat for manufacturing/curing. The behavior of these polymer composite materials is highly dependent on curing process as it affects evolution of material properties as well as residual stresses and deformation. Various cure process parameters, mainly related to cure thermal cycle, need to be optimized to get the desired properties of these structures. In this paper, the polymer cure process is explicitly modeled through finite element method. Its effects at the structural level are captured by modeling thermo-chemical-mechanical analysis through multiple length scales. The multi-scale analysis is carried out by surrogate models to reduce run time. In this study, non-dominated sorting genetic algorithm II is used for multi-objective cure process optimization. The objectives are to minimize the spring-in angle and minimize the process time with achieving degree of cure above given requirement. Insights from such optimization can be utilized by product designers as well as manufacturers to take timely decisions to improve the performance of these composite structures.