Machine Learning Operations (MLOps) Engineer
Core
Build and operate the infrastructure, release processes, and evaluation systems that move AI/ML models from training to deployed capability in air-gapped, restricted-network environments for national security logistics.
Role type
Senior MLOps Engineer (Defense/Security)
Builds
Production ML systems, LLM inference stacks, CI/CD pipelines, and evaluation harnesses for logistics and doctrinal data.
Domain
National Security / Defense Logistics / AI Infrastructure
Deliverable
production ML models
Required skills
MLOps, Python, Kubernetes, Infrastructure as Code, AWS ML/Azure, GPU infrastructure, Air-gapped/Disconnected deployment, Model evaluation & monitoring, Data lineage & versioning
Preferred skills
LLM serving optimization (vLLM, quantization), Retrieval-grounded systems, Edge/on-prem deployment, ATO/Continuous authorization support, Palantir Foundry, PostgreSQL, NATS, ArgoCD
Technologies
AWS SageMaker, EKS, vLLM, Kubernetes, GitOps, Docker, Python, PostgreSQL, NATS, ArgoCD
Responsibilities
Own model training, fine-tuning, and batch inference infrastructure; Build CI/CD for models and pipelines; Build and own the evaluation harness for regression and LLM-as-judge; Deploy and operate ML systems in IL5/IL6 environments; Support ATO and continuous-authorization work.
Seniority
Senior, hands-on IC