Worked on the amazon-braket-sdk-python repository with a focus on improving stability and compatibility for SageMaker environments. Addressed a critical issue by pinning the cloudpickle dependency to version 2.2.1 in setup.py, which prevented failures caused by newer cloudpickle releases and ensured consistent runtime behavior for machine learning workloads. The work emphasized reliability and maintainability, prioritizing robust deployment experiences over new feature development during the period. Utilized Python and applied expertise in dependency management and Python packaging to enhance environment stability. Documented the rationale for the dependency pin, supporting clear release hygiene and aligning with business priorities for predictable ML deployments.