Sr. MLOps Engineer - Contract role - Remote - Immediate start (Faridabad)

The Sr. MLOps Engineer will build and own the infrastructure layer that bridges Data Science model development with operational scoring pipelines — ensuring that Paragon's predictions are delivered at scale, with full auditability and drift detection. Key Responsibilities: - Design and implement model deployment pipelines from Azure ML to production scoring endpoints, including versioning and rollback capabilities - Build and maintain model monitoring infrastructure for drift detection, prediction quality tracking, and data quality alerting - Manage Feature Store operations: pipeline scheduling, freshness SLAs, and serving layer for both batch and near-real-time inference - Integrate Paragon scoring outputs into SCOUT operational workflows via the TPL Intel API adapter pattern - Implement automated retraining triggers based on drift thresholds or scheduled cadences - Maintain environment parity across development, staging, and production for all ML workloads on Azure - Collaborate with Infrastructure (DevOps) to ensure ML compute environments are right-sized, cost-controlled, and compliant - Build observability dashboards for model performance and pipeline health in Azure Monitor or Power BI Requirements: - 4+ years of MLOps or ML infrastructure engineering experience - Strong experience with Azure ML, Azure DevOps, and Python-based pipeline orchestration - Familiarity with feature stores, model registries, and serving infrastructure - Experience in regulated data environments (healthcare, financial services) preferred - Solid understanding of CI/CD principles applied to ML workflows - Solid communication skills for async collaboration with U.S.-based Data Science and Engineering teams Share resume to / +91 9924488801