AI/ML Engineer

Job Summary For AI/ML Engineer Design, build, and deploy AI-driven data reconciliation and automation solutions as part of a large-scale data migration program. Develop anomaly detection pipelines, automated validation workflows, and AI-assisted data mapping tools to improve data quality and accelerate migration. Work hands-on with Azure-based AI/ML platforms including Azure Machine Learning, Databricks, Data Factory, Synapse Analytics, and Delta Lake. Monitor model performance, manage drift, and ensure auditability in regulated environments. Collaborate with technical and business stakeholders to translate requirements into intelligent automation logic. Deliver executive-level insights via dashboards and reporting tools. Mentor team members and support knowledge transfer to enhance internal AI/ML capabilities. Build and optimize advanced T-SQL and PL/SQL solutions across SQL Server and Oracle for high-volume ETL and dashboard workloads. Engineer rule-based exception classification pipelines and construct prioritized work queues based on stakeholder scenarios. Design cloud-native ingestion pipelines and manage data lineage with Azure Purview; deploy microservices using Docker and AKS with CI/CD workflows. Implement and monitor production models using Azure Monitor, MLflow, and custom drift detection, ensuring ongoing model accuracy and compliance. Minimum Requirements 6+ years in applied AI/ML pipeline development for data reconciliation, with production experience in anomaly detection and exception classification models (PyTorch, Scikit-learn, Azure ML). 6+ years in Azure data platform engineering (Databricks, Data Factory, Synapse, Delta Lake) designing automated, auditable workflows. 10+ years advanced T-SQL and PL/SQL experience for SQL Server/Oracle, including performance optimization for ETL/dashboard workloads. 6+ years developing rule-based exception handling and automated validation logic for multiple stakeholder scenarios. 4+ years building cloud-native ingestion pipelines (Azure Data Factory, Service Bus, Functions), managing data lineage, and deploying microservices (Docker, AKS, CI/CD). 4+ years production model monitoring, drift detection, and experiment tracking (Azure Monitor, MLflow, custom drift detectors). Show more Show less