To set up a CI/CD pipeline for deploying deep learning models, I’d utilize tools like Jenkins or GitLab CI for orchestration, ensure model versioning through a model registry like MLflow, and implement training and validation stages as part of the pipeline. Rollback mechanisms can be achieved by maintaining previous model versions and using automated monitoring to trigger rollbacks if performance drops.