ML Ops Engineer

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Global:IQ is seeking an MLOps Engineer to build and maintain the operational infrastructure for their AI-driven media intelligence platform. The role focuses on establishing end-to-end ML pipelines, model monitoring, and governance standards from the ground up in a production environment. You will collaborate closely with Data Science and Engineering teams to ensure reliable deployment and scaling of ML models.

• Build automated pipelines for model training, validation, and deployment using AWS services like SageMaker and Step Functions.
• Implement model monitoring, alerting, and automated recovery systems for latency, data quality, and drift.
• Establish MLOps governance controls including model lineage, reproducibility, and audit trails.
• Develop self-serve tooling for Data Science teams, including feature stores and model registries.
• Mentor junior engineers and promote best practices in ML-specific CI/CD and IaC.

• Proven experience operationalizing ML models in production environments.
• Strong proficiency in Python for production-quality, testable code.
• Deep expertise in AWS cloud services (SageMaker, Lambda, ECS/EKS, Step Functions).