Description

You will design, develop, and optimize scalable machine learning workflows.

Responsibilities

• Build and deploy ML pipelines using Delta Lake, MLflow, notebooks, and Databricks Jobs.
• Apply Databricks architecture knowledge to tune and support production ML solutions.
• Operationalize ML models at scale by collaborating with data scientists and engineers.
• Migrate legacy training and scoring workflows into unified Databricks pipelines.
• Ensure model reproducibility, governance, monitoring, and security within Databricks.

Required Skills

• 5+ years of deep, hands-on experience with Azure Databricks for ML deployment.
• Strong Python skills, including libraries like scikit-learn, pandas, and PySpark.
• Proficiency in SQL for data preparation and analysis.
• Experience orchestrating end-to-end ML pipelines (preprocessing, training, validation, deployment).
• Solid understanding of MLOps principles, including versioning and CI/CD for ML.
• Experience with Delta Lake, MLflow, and Spark ML/PyTorch/TensorFlow integrations.
• Familiarity with Azure cloud services (Data Lake, Azure ML, Data Factory).
• Knowledge of feature engineering and automated model retraining in production.
• Proven track record delivering ML models in enterprise environments.

Key Skills

Education

Any Graduate