This role applies modern machine learning techniques, data engineering practices, and platform-based development to deliver scalable, secure, and operational AI solutions.

The ideal candidate will have hands-on experience with Palantir Foundry, strong Python and data pipeline development skills, and the ability to integrate, train, deploy, and optimize ML models across enterprise environments. This role supports both development and operationalization of AI/ML capabilities to enable mission-critical decision support and automation.

Key Responsibilities

• Design, develop, train, and deploy machine learning models using enterprise data platforms and modern ML frameworks
• Build and maintain robust ETL/ELT pipelines and complex data workflows, ensuring data quality, lineage, and version control
• Develop pipelines and custom logic within Palantir Foundry and Forge platforms
• Define and leverage Foundry Ontology to model, organize, and link enterprise data
• Build user workflows and operational applications in Foundry (low-code/no-code + custom code)
• Implement and integrate LLM-based capabilities via Python-based APIs and libraries
• Conduct feature engineering, model evaluation, and performance tuning
• Collaborate with data scientists, software engineers, and mission stakeholders to deploy AI into production environments
• Implement cloud-based ML deployment best practices (AWS/Azure)
• Develop dashboards, visualizations, and interactive analytic tools for stakeholders
• Ensure system and data security practices align with federal cybersecurity standards
• Document technical processes, pipelines, and model lifecycle procedures

Required Qualifications

• Must hold a current Secret Clearance
• BA/BS in Computer Science, Engineering, Data Science, Mathematics, or related field OR equivalent experience
• 5+ years' experience with machine learning, data engineering, or platform-based AI delivery
• Hands-on experience with Palantir Foundry
• Proficiency in Python for ML and pipeline development
• Experience implementing and calling LLM APIs and LLM-driven applications
• Proficiency with SQL, PySpark / Spark
• Experience building data pipelines and integrating large-scale data from multiple sources
• Experience with cloud environments (AWS and/or Azure)
• Experience with Machine learning model design, training, and deployment
• Experience with LLM integration & API-driven AI development
• Experience with ETL/ELT pipeline engineering
• Experience with data quality, governance, and version control
• Experience with full-stack data platform application development
• Strong problem-solving and collaboration skills
• Clear, mission-focused communication

Desired Qualifications

• Data security best practices and secure AI deployment
• Model monitoring and MLOps tools
• Dashboards and analytic tools (e.g., Foundry Contour, Power BI, Tableau)
• Palantir Foundry pipelines & ontology modeling