- Design End-to-End AI/ML Solutions using scalable architectures covering data ingestion, feature engineering, model development, training, deployment, and monitoring using Azure ML, Databricks, Synapse, ADF, and Snowflake (Snowpark, Streams, Tasks).

- Leverage AI Foundry for enterprise-grade AI workflows, model orchestration, and automation.

- Define and implement frameworks for model versioning, experiment tracking, retraining pipelines, CI/CD, and monitoring using ML flow, Azure ML Pipelines, AI Foundry, Docker, Kubernetes, and GitHub Actions.

- Evaluate and recommend optimal ML algorithms, frameworks, and cloud services (e. g., Azure ML, Snowflake, Databricks).

- Drive AI Strategy, collaborate with business and data stakeholders to align AI/ML initiatives and roadmap with organisational goals and measurable outcomes.

- Ensure Quality, Performance, C Compliance are implemented using standards for data privacy, model fairness, explainability, and operational excellence.

- Mentor and Lead Teams on solution design, best practices, and reusable accelerators.

Requirements :

- Bachelor's or master's degree in computer science, Data Science, or related field.

- 8+ years in data science, ML, or AI engineering, with at least 2 years in a solution/architect role.

- Hands-on experience with Python, SQL, ML frameworks (TensorFlow, PyTorch, Scikit-learn), and MLOps tools (MLflow, Azure ML Pipelines, Docker/Kubernetes).

- Proven experience deploying and optimizing ML models in the Azure cloud and integrating with Snowflake data platforms.

- Solid understanding of data pipelines, feature stores, cloud-native AI/ML architectures, and ETL workflows.