MLOps Engineer

To support a growing AI/ML infrastructure, the full-time remote MLOps Engineer will design, provision, and maintain the Azure environment while building end-to-end ML pipelines and ensuring security compliance. Key responsibilities Design and provision Azure resource groups, networking, and identity management for AI/ML workloads Build and implement end-to-end ML pipelines, including model training, evaluation, and deployment workflows Monitor Azure consumption and set budgets to optimize spending against the approved AI CoE budget Required qualifications Experience with Azure Machine Learning and Azure resource management Proficiency in building ML pipelines using Azure ML Pipelines or Fabric Data Factory Knowledge of data encryption, security compliance, and IT governance frameworks Familiarity with Power BI and semantic model creation for analytics Experience in developing PySpark and Python notebooks for data analysis and feature engineering