Developed a hybrid quantum-enhanced ensemble classification tutorial for the Qiskit/documentation repository, enabling researchers to experiment with advanced grid stability workflows using Multiverse Computing’s Singularity Machine Learning. The work involved designing an end-to-end tutorial flow in Python, providing reproducible experiment samples and strengthening documentation for quantum machine learning use cases. By improving onboarding materials and documentation structure, the contribution facilitated faster adoption and cross-team collaboration within the quantum ML research community. The technical approach emphasized clarity and reproducibility, leveraging skills in Python programming, data analysis, and quantum computing to address complex workflow challenges and support advanced research and development needs.