Worked on the neuralmagic/gateway-api-inference-extension repository to enhance the reliability and coverage of the Scheduler Scorer’s testing framework. Focused on backend development using Go, the work involved introducing a dummy scorer and picker, expanding validation for the full Result structure, and implementing load-based scoring tests to capture edge cases. Addressed test setup issues and reduced flakiness, resulting in more stable and trustworthy test outcomes. These improvements increased confidence in the scoring logic under varying load conditions, supporting safer and faster production deployments. Emphasized robust testing practices and backend reliability, leveraging Go and modern testing methodologies throughout the development process.