Worked on stability improvements for PJRT within the Intel-tensorflow/tensorflow and Intel-tensorflow/xla repositories, focusing on resolving critical bugs rather than delivering new features. Addressed segmentation faults by correcting callback size references in PJRT receive handling, which stabilized runtime behavior and reduced crash risk for machine learning workloads. Utilized C++ for both debugging and implementation, coordinating fixes across repositories through a single pull request and ensuring consistent behavior via regression testing. Emphasized maintainability and reliability, resulting in improved uptime and predictability for TensorFlow and XLA integrations. Demonstrated expertise in bug fixing, callback handling, and cross-repository software debugging.