Principal MLOps Engineer

Role: Principal MLOps Engineer

Help design, deploy, and mature Raft’s end-to-end machine learning platform and MLOps infrastructure for production use in defense environments.

Responsibilities

• Design, build, and maintain secure, scalable MLOps infrastructure and deployment pipelines for production ML systems.
• Mature the internal ML platform and model lifecycle capabilities, including:
  • model packaging
  • registry/catalog workflows
  • deployment
  • monitoring
  • operational support
• Deploy and manage ML workloads on Kubernetes, including GPU-enabled clusters.
• Support model serving and inference infrastructure across ML use cases (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 operational deployment.
• Improve observability, reliability, security, and maintainability of ML infrastructure and services.
• Evaluate and standardize runtime patterns, serving frameworks, and deployment architectures for production ML.
• Contribute to infrastructure decisions across edge, on-prem, and cloud deployment environments.
• Apply compliance-driven deployment practices and secure software supply chain requirements.
• Provide hands-on customer support in advanced deployment scenarios.

Requirements

• 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.

Location / Eligibility

• U.S.-based position with work conducted in the continental U.S.
• U.S. citizenship required for employment eligibility.