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

MLOps Engineer — AI/ML Systems & Deployment (TS/SCI Preferred) Dayton, OH (On-site Preferred) | Remote Eligible (U.S.-based, Clearance-Ready) Clearance-Eligible Role | Mission-Critical AI/ML Systems About the Role At Rackner, we build systems where advanced technologies move beyond prototypes and into real-world operational use. We are seeking an MLOps Engineer to support the deployment and lifecycle management of AI/ML systems within a secure, mission-focused environment. This is not a research role. This is where models become reliable, deployable, and auditable systems. You will operate at the intersection of: • machine learning • cloud-native infrastructure • distributed systems …and ensure AI/ML systems are production-ready in environments where reliability and performance matter. 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 • Deploy models into secure and constrained environments Transition workflows from experimentation containerized pipelines production systems Enable both batch and real-time inference architectures Engineer for Reliability • Design systems for reproducibility, auditability, and stability • Monitor model performance and system health using Prometheus, Grafana, OpenTelemetry • Detect and resolve issues such as model drift and system degradation Build Cloud-Native ML Infrastructure • Deploy and manage Kubernetes-based ML workloads • Containerize pipelines using Docker • Support scalable training and inference workflows Establish Data Discipline • Support feature engineering and dataset preparation • Implement data versioning and governance practices (e.g., lakeFS) • Apply metadata and data management standards Create Repeatable Systems • Develop runbooks, playbooks, and documentation • Build systems that are operationally sustainable and transferable What You Bring Core Experience • Experience deploying ML systems into production environments • Strong programming skills in Python • Hands-on experience with: • ML pipeline tools (Kubeflow, Airflow, Argo) • Experiment tracking tools (MLflow, ClearML) Infrastructure & Systems • Experience with Kubernetes and containerized systems (Docker) • Familiarity with CI/CD pipelines • Understanding of distributed systems and scalable architectures ML Application Exposure • Experience working with: • LLMs or transformer-based models • Computer vision systems (YOLO, Faster R-CNN) • Focus on deployment and integration, not pure research Mindset • Systems thinker who prioritizes reliability over novelty • Comfortable operating in complex, evolving environments • Focused on delivering real-world outcomes Clearance Requirements • Active TS/SCI clearance strongly preferred • Candidates with an active Secret clearance may be considered and supported for upgrade • Candidates without an active clearance must be: • U.S. citizens • eligible to obtain and maintain a clearance • able to work in a CAC-enabled or secure environment Note: Start timelines and work scope may vary depending on clearance status and program requirements Why This Role Matters (What You Get) This role is a career accelerator for engineers who want to: • Move beyond experimentation and own production systems • Work across ML, infrastructure, and deployment pipelines • Build in high-trust, secure environments • Develop high-demand MLOps expertise in constrained systems • Deliver systems that are used, not just built Who We Are Rackner is a software consultancy that builds cloud-native solutions for startups, enterprises, and the public sector. We are an energetic, growing team focused on solving complex problems through: • Distributed systems • DevSecOps • AI/ML • Cloud-native architecture Our approach is cloud-first, cost-effective, and outcome-driven, delivering systems that scale and perform in real-world environments. Benefits & Perks • 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 Apply If you're an engineer who wants to move from building models owning production systems, we'd like to connect. #MLOps #MachineLearning #Kubernetes #AIEngineering #CloudNative #DevSecOps #ArtificialIntelligence #DataEngineering #DefenseTech #NationalSecurity #AIInfrastructure #Hiring #TechCareers