ML Engineer

📋 Description

• Build scalable data and ML infrastructure using Databricks.
• Design medallion architecture Bronze/Silver/Gold for data processing.
• Develop automated pipelines for structured and unstructured data sources.
• Create robust ETL/ELT workflows with Spark for batch and streaming data.
• Build data quality monitoring across data and ML lifecycle.
• Implement MLOps practices with MLflow and Databricks for training deployment monitoring.

🎯 Requirements

• 5+ years of technical experience; 3+ years building production data pipelines and ML infra with Databricks.
• Strong data engineering with Python, PySpark, Spark SQL; medallion architecture and modern data platform patterns.
• Production ML systems: deployment, monitoring, and MLOps in cloud environments.
• Data architecture expertise; scalable data processing and governance frameworks.
• Experience integrating Qlik, Tableau, PowerBI, Palantir Foundry or similar.

🎁 Benefits

• Competitive and comprehensive benefits package.
• Collaborative, supportive, family-like culture.
• Growth, learning, and career development opportunities.
• Equal Opportunity Employer/Protected Veterans/Disabilities.