MLOps Engineer — AI/ML Systems Deployment (TS/SCI Preferred)

Job summary

MLOps Engineer to operationalize AI/ML systems in secure environments, focusing on deploying models and building production-grade ML pipelines.

Qualifications

• U.S. citizenship
• Experience in deploying ML systems or production software
• Hands-on experience with Docker and containerized deployment
• Familiarity with Kubernetes or cloud-native environments
• Understanding of CI/CD and automation
• Active TS/SCI clearance preferred
• Active Secret clearance with eligibility for upgrade

Responsibilities

• Deploy AI/ML models and applications into secure environments
• Move workflows to containerized, repeatable deployment pipelines
• Support batch and real-time inference architectures
• Bridge model development and platform operations
• Build and operate production-grade ML pipelines
• Support model versioning and lifecycle governance
• Deploy and support Kubernetes-based ML workloads
• Containerize models and services using Docker
• Monitor model and system performance post-deployment
• Support observability using monitoring tools
• Deploy AI/ML systems in secure environments
• Develop deployment documentation and operational playbooks

Skills

Security clearance

Relocation