MLOps Engineer

Job Summary

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