Worked on the wandb/wandb repository to deliver targeted backend improvements focused on experiment management and observability. Addressed two critical bugs by ensuring that sweep configurations created via the SDK now properly honor the distribution parameter, reducing the risk of misconfigured experiments and improving reproducibility. Enhanced the Hyperband stopping algorithm’s logging by restructuring debug output to emit complete lines, which streamlines troubleshooting and clarifies early termination events for large-scale machine learning runs. Leveraged Python for backend development, code refactoring, and advanced debugging, with an emphasis on robust logging and machine learning operations to support more reliable and transparent experimentation workflows.