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

MLOps Engineer role at Rackner, responsible for deploying and managing AI/ML systems in a secure, mission-focused environment. Own the ML lifecycle, build and operate production-grade ML pipelines, and ensure AI/ML systems are production-ready in environments where reliability and performance matter.

Requirements

• Experience deploying ML systems into production environments
• Strong programming skills in Python
• Hands-on experience with ML pipeline tools (Kubeflow, Airflow, Argo)
• Experience with Kubernetes and containerized systems (Docker)
• Understanding of distributed systems and scalable architectures

Benefits

• 100% covered certifications & training aligned to your role
• 401(k) with 100% match up to 6%
• Highly competitive PTO
• Comprehensive Medical, Dental, Vision coverage
• Life Insurance + Short & Long-Term Disability
• Home office & equipment plan
• Industry-leading weekly pay schedule