ML Engineer

About this role

Agile Defense seeks an ML Engineer to design and deploy scalable data and ML infrastructure supporting national defense missions. You'll build production-grade pipelines, implement MLOps best practices, and enable advanced analytics by integrating Databricks, Apache Spark, and enterprise platforms like Palantir Foundry.

What you'll do

• Design and implement medallion architecture data pipelines using Databricks for batch and streaming data processing
• Build MLOps systems including automated model training, validation, deployment, and monitoring with MLflow
• Create data quality monitoring, governance frameworks, and metadata management systems
• Develop scalable ML inference systems handling high-volume, low-latency predictions in production
• Design data models supporting both machine learning and business intelligence analytics
• Integrate Databricks systems with enterprise platforms including Palantir Foundry, Tableau, and data warehouses

What they're looking for

• Python, PySpark, and Spark SQL
• Databricks and Apache Spark distributed computing
• Production ML systems and MLOps practices
• Data architecture and pipeline design
• Data governance and metadata management
• Integration with BI platforms (Tableau, PowerBI, Qlik Sense)
• Cloud environments and scalable data processing
• Palantir Foundry or similar analytics platforms