Principal MLOps Engineer

Role Overview

Raft is hiring a Principal MLOps Engineer (U.S.-based; requires U.S. citizenship and work conducted within the continental U.S.). The role will help design, deploy, and mature Raft’s end-to-end ML platform and MLOps infrastructure for mission-critical AI and data platforms supporting DoD operators.

Responsibilities

• Design, build, and maintain secure, scalable MLOps infrastructure and production deployment pipelines
• Mature internal ML platform and model lifecycle capabilities, including:
  • model packaging
  • registry/catalog workflows
  • deployment, monitoring, and operational support
• Deploy and manage ML workloads on Kubernetes, including GPU-enabled clusters
• Build/maintain model serving and inference infrastructure (traditional ML, computer vision, speech/audio, and LLM-based systems)
• Create CI/CD workflows for ML services, model artifacts, and platform components
• Partner with ML engineers, software engineers, and product teams to move models from experimentation to reliable production
• Improve observability, reliability, security, and maintainability across ML infrastructure and services
• Evaluate/standardize runtime patterns, serving frameworks, and deployment architectures
• Contribute to infrastructure decisions across edge, on-prem, and cloud environments
• Support compliance-driven deployment practices and secure software supply chain requirements for defense environments

Requirements

• 7+ years hands-on experience in software engineering, platform engineering, DevOps, MLOps, or related roles
• 5+ years experience with Docker and Kubernetes in production
• 5+ years supporting enterprise cloud infrastructure/applications on AWS, Azure, or similar

Role Focus / Ideal Fit

• Strong understanding of both production infrastructure for ML systems and the practical needs of ML engineers shipping and operating models