ML Ops Engineer

Role : ML Ops Support EngineerWe are looking for a skilled MLOps Support Engineer to join our team. This role involves monitoring and managing MLmodel operational pipelines in AzureML and MLflow, with an emphasis on automation, integration validation, and CI/CDpipeline management. The ideal candidate will be technically sound in Python, Azure CLI, and MLOps tools, and capableof ensuring stability and reliability in model deployment lifecycles.

*Objectives of the role:*

 Support and monitor MLOps pipelines in AzureML and MLflow Manage CI/CD pipelines for model deployment and updates Handle model registry processes, ensuring best practices for versioning and tracking Perform testing & validation of integrated endpoints to ensure non-functional stability Automate monitoring and upkeep of ML pipelines to relieve the data science team Troubleshoot and resolve pipeline and integration-related issues

*Responsibilities:*

 Support production ML pipelines using AzureML and MLflow Configure and manage model versioning and registry lifecycle Automate alerts, monitoring tasks, and routine pipeline operations Validate REST API endpoints for ML models Implement CI/CD workflows for ML deployments Document and troubleshoot operational issues related to ML services Collaborate with data scientists and platform teams to ensure delivery continuity

*Required Skills & Qualifications:*

 Proficiency in AzureML, MLflow, and Databricks Strong command over Python Experience with Azure CLI and scripting Good understanding of CI/CD practices in MLOps Knowledge of model registry management and deployment validation 3–5 years of relevant experience in MLOps environmentsSkills that are good to have, but not mandatory: Exposure to monitoring tools (e.g., Azure Monitor, Prometheus) Experience with REST API testing (e.g., Postman) Familiarity with Docker/Kubernetes in ML deployments