To set up a robust MLOps pipeline, you should consider factors such as data quality, model versioning, reproducibility, and automation. You should also establish clear processes for testing, deployment, and monitoring of your models. It is important to involve all stakeholders, including data scientists, engineers, and business leaders, in the design and implementation of your MLOps pipeline.