Designing and implementing a cloud-native data science platform that supports the full Machine Learning (ML) lifecycle, including model development, training, deployment, and monitoring. Supporting the development of our self-service platform SDK for the data science platform and operation on Google Cloud Platform and Microsoft Azure. Collaborating with data scientists and ML experts to promote the use of our data science platform, bringing ML models into production-ready applications, ensuring scalability and performance. Creating software solutions that enable hybrid processing in multi-cloud and on-premises environments. Integrating security standards, policies, and controls into our service offerings. Focusing on delivering high-quality code and robust architecture. Collaborating in a cross-functional and agile team