Sr MLOps Engineer

📋 Description

• Design, build, and maintain infra and tools for the ML lifecycle from development to deployment
• Operate production-grade Kubernetes cluster including CNI networking and storage
• Deploy ML orchestration tooling (e.g., Metaflow) and storage for reproducible workflows
• Validate GPU node health across multiple hardware types and standardize drivers/CUDA
• Port workflows, migrate datasets/artifacts, and roll out tool updates with engineering teams
• Write runbooks, architecture docs, and disaster recovery procedures

🎯 Requirements

• 3+ years in infrastructure, DevOps, or MLOps roles or equivalent
• Production Kubernetes experience (networking, storage, RBAC, troubleshooting)
• Python and/or Bash scripting; IaC tools (Ansible, Helm, Terraform, or similar)
• Hands-on with distributed storage (S3, MinIO, NetApp, or similar)
• CI/CD pipelines experience (GitLab CI, ArgoCD, or equivalent)
• Linux administration and networking fundamentals; strong communication/doc skills

🎁 Benefits

• Onsite weekly schedule with set hours; close collaboration with cross-functional teams
• Equal opportunity employer; vaccination context noted; covered by company policies