• Responsible for managing MLOps workflows, tools, and production support processes for ML solutions.
• Ensure day-to-day stability, reliability, and performance of ML models and pipelines.
• Manage model lifecycle controls, including versioning, lineage, reproducibility, monitoring, and governance.
• Develop incident handling, recovery, and escalation procedures for ML-related issues.
• Support data quality, lineage tracking, and governance practices across the ML lifecycle.

Strong MLOps and production operations focus

• Responsible for designing, implementing, and managing MLOps workflows, tools, and operational processes for ML and GenAI solutions.
• Oversee the day-to-day stability, reliability, and operational health of ML models and ML pipelines.
• Manage model lifecycle operations, including model registration, versioning...