Principal MLOps Engineer

Raft is seeking a Principal MLOps Engineer to design, build, and maintain secure, scalable MLOps infrastructure for mission-critical AI and data platforms supporting the Department of Defense. The role involves deploying ML workloads on Kubernetes, building CI/CD pipelines, and working closely with ML engineers to move models from experimentation to production. The position requires U.S. citizenship and work within the continental U.S.

• Design, build, and maintain secure, scalable MLOps infrastructure and deployment pipelines for production ML systems.
• Help mature Raft’s internal ML platform and model lifecycle capabilities, including model packaging, registry/catalog workflows, deployment, monitoring, and operational support.
• Deploy and manage machine learning workloads on Kubernetes, including GPU-enabled clusters.
• Support model serving and inference infrastructure for a range of ML use cases.
• Build and maintain CI/CD workflows for ML services, model artifacts, and platform components.
• Partner closely with ML engineers, software engineers, and product teams to move models from experimentation to reliable operational deployment.
• Improve observability, reliability, security, and maintainability across ML infrastructure and services.
• Help evaluate and standardize runtime patterns, serving frameworks, and deployment architectures.
• Contribute to infrastructure decisions across edge, on-prem, and cloud-hosted environments.