Developed and delivered the Chronos-2 time series forecasting example for the modal-labs/modal-examples repository, focusing on both real-time inference and batch processing workflows. The work involved refactoring the project structure by relocating the chronos directory under misc, streamlining navigation and ongoing maintenance. A concise forecasting tutorial was added to accelerate onboarding for users and developers, demonstrating an end-to-end workflow for time series prediction. Collaborated cross-functionally to enhance code quality and documentation. The project leveraged Python, AWS, and Modal, applying data science and machine learning techniques to provide a practical, accessible example for time series forecasting within the repository.