Principal MLOps Engineer

📋 Description

• Design, build, and maintain secure MLOps infra for production ML
• Deploy ML workloads on Kubernetes, including GPU clusters
• Build CI/CD workflows for ML services and platform components
• Support model serving/inference infra for ML use cases
• Collaborate with ML, software, and product teams to deploy models
• Improve observability, reliability, security, and maintainability

🎯 Requirements

• 7+ years in software engineering, platform, DevOps, or MLOps
• 5+ years Docker and Kubernetes in production
• 5+ years deploying enterprise cloud infra in AWS or Azure
• Strong Kubernetes provisioning and troubleshooting in production
• Experience deploying ML workloads on Kubernetes and building ML platforms
• Top Secret clearance eligibility; ability to obtain Security+ within 90 days

🎁 Benefits

• Highly competitive salary
• Fully covered healthcare, dental, and vision
• 401(k) with company match
• Take as you need PTO + 11 paid holidays
• Education & training benefits
• Annual tech/gadget budget