Your data science team is working on optimizing a PyTorch model for image classification using a pre-trained ResNet model. The team is under tight budget constraints and needs to ensure the solution is scalable for future projects. Additionally, the solution must support custom containers for flexibility. What is the most effective approach to perform hyperparameter tuning in this scenario? Choose the best option.