AI / Machine Learning Engineer

About the role

Job Description

We are seeking an experienced Artificial Intelligence / Machine Learning Engineer with strong expertise in AI/ML pipeline development, LLMs, model evaluation, intelligent automation, and data reconciliation.The ideal candidate will design, develop, and deploy AI-driven solutions that automate data validation, anomaly detection, exception classification, and source-to-target mapping. This role requires strong hands-on experience with Azure AI/ML and data engineering platforms and the ability to build scalable, auditable solutions for large-scale data migration programs.

Key Responsibilities

Design and deploy ML-based anomaly detection pipelines to identify data discrepancies early in the ETL and migration lifecycle.

Develop AI-assisted field mapping and classification solutions for source-to-target data migration.

Build automated data quality scoring and reconciliation pipelines.

Apply LLM evaluation methodologies and judge-model frameworks to validate AI-generated outputs.

Develop exception classification and prioritized work queue solutions.

Monitor production models for performance degradation and model drift.

Build real-time dashboards for migration quality and data integrity monitoring.

Translate stakeholder requirements into automated validation and reconciliation logic.

Develop scalable and maintainable AI/ML solutions using Azure technologies.

Create technical documentation and participate in knowledge transfer activities.

Required Skills & Qualifications

12+ years of overall senior-level IT/engineering experience.

6+ years of hands-on experience in AI/ML pipeline development and production deployment.

Strong experience with PyTorch, Scikit-learn, Azure Machine Learning, and anomaly detection.

6+ years of experience with Azure Databricks, Azure Data Factory, Azure Synapse Analytics, and Delta Lake.

10+ years of advanced SQL, T-SQL, and PL/SQL development using SQL Server and Oracle.

Experience building automated and auditable data reconciliation and validation frameworks.

Strong knowledge of LLMs, AI model evaluation, model monitoring, and drift detection.

Experience with MLflow, Azure Monitor, and production ML lifecycle management.

Experience with Azure Functions, Azure Service Bus, Azure Purview, Docker, AKS, and CI/CD.

Ability to work with large-scale datasets and regulated environments.

Strong communication and stakeholder management skills.

Master's degree in Computer Science, Information Technology, Data Science, or related field.

Preferred Skills

Great Expectations and pytest for automated data quality validation.

Legacy/mainframe or COBOL data migration experience.

Azure Purview and data lineage management.

Delta Lake optimization and Parquet performance tuning.

Azure Key Vault and Managed Identity.

Experience in Financial Services, Government, Healthcare, or other regulated environments.

Key Skills: AI/ML, Machine Learning, LLM, Generative AI, Azure Machine Learning, Azure Databricks, Azure Data Factory, Azure Synapse, PyTorch, Scikit-learn, MLflow, Anomaly Detection, Data Reconciliation, Model Drift, Data Quality, SQL, PL/SQL, Azure Purview, Docker, AKS, CI/CD.