• Operationalize ML and LLM-based workloads, gather stakeholder feedback, and drive them into production-ready systems • Create, manage, and improve continuous integration and delivery pipelines to support rapid iteration and deployment of ML models and services • Implement observability practices for ML systems, including monitoring, logging, and alerting • Maintain and improve the infrastructure for ML/LLM evaluation sets, including versioning, automated validation pipelines, and continuous quality checks across the model lifecycle • Ensure high data quality and monitor performance of ML workloads in production • Work closely with ML engineers, data scientists, and cross-functional teams to build impactful solutions • Participate in an on-call rotation to ensure system uptime and reliability • Additional projects and responsibilities as business needs require