Principal MLOps Engineer

Role Overview

Raft is hiring a Principal MLOps Engineer to design, deploy, and mature its end-to-end ML platform and MLOps infrastructure for Department of Defense use cases. The role spans Kubernetes-based deployments, GPU-enabled infrastructure, model serving, secure production operations, and CI/CD for ML artifacts.

What You’ll Do

• Design, build, and maintain secure, scalable MLOps infrastructure and deployment pipelines for production ML systems
• Mature Raft’s internal ML platform and model lifecycle capabilities (packaging, registry/catalog workflows, deployment, monitoring, operational support)
• Deploy and manage ML workloads on Kubernetes, including GPU-enabled clusters
• Own model serving and inference infrastructure across ML use cases such as:
  • traditional ML
  • computer vision
  • speech/audio
  • LLM-based systems
• Build 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 production
• Improve observability, reliability, security, and maintainability across ML infrastructure and services
• Evaluate and standardize runtime patterns, serving frameworks, and deployment architectures
• Influence infrastructure decisions across edge, on-prem, and cloud deployment environments
• Support compliance-driven deployment practices and secure software supply chain requirements in defense environments

What We’re Looking For

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

Nice-to-Haves (implied)

• Strong understanding of both ML production infrastructure and the practical needs of ML engineers delivering models
• Experience with secure production operations and defense/compliance-oriented environments