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

Job description

MLOps Engineer — AI/ML Systems & Deployment (TS/SCI Preferred) Dayton, OH (On-site Preferred) | Remote Eligible (CAC-Ready Candidates) Mission Environment | AI/ML Infrastructure | National Security Impact About the Role: At Rackner, we are building the operational backbone that turns AI/ML capability into real-world mission outcomes. We are seeking an MLOps Engineer to own the lifecycle of AI/ML systems—from experimentation to deployment—within a mission-critical, classified environment supporting Air Force and NASIC-aligned programs. This is not a research role; This is where models become reliable, deployable, auditable systems. You will operate at the intersection of: …and ensure that AI/ML systems work in the environments where failure is not an option. - Machine learning - Distributed systems - Cloud-native infrastructure What You’ll Do: Own the ML Lifecycle (End-to-End): - Build and operate production-grade ML pipelines - Orchestrate workflows using Kubeflow, Airflow, or Argo - Implement model versioning, lineage, and reproducibility standards Operationalize AI/ML Systems: Engineer for Reliability, Not Just Performance - Deploy models into mission environments (including cons...