Senior DevOps Engineer

Job Summary

Owning the infrastructure that supports VisionAI in production, the full-time Senior DevOps/MLOps Engineer will manage the GKE platform, build edge fleet management systems, and run the MLOps path for computer vision, all while working remotely.

Key responsibilities

• Own and operate the GKE platform across per-customer Google Cloud projects, including provisioning new customer clusters with Terraform, Helm, and GitOps
• Build edge fleet management systems to automate deployment, monitoring, and updates across a growing fleet of on-site edge servers
• Run the MLOps path for computer vision by creating repeatable pipelines for GPU workloads and CV models from the ML team to inference nodes and the edge fleet

Required qualifications

• 8+ years in DevOps, SRE, platform, or infrastructure engineering with real production ownership
• Expert-level Kubernetes experience in production, preferably with managed Kubernetes such as GKE
• Strong Infrastructure-as-Code experience with Terraform and Helm
• Deep experience on a major cloud provider (GCP preferred; strong AWS or Azure background acceptable)
• Hands-on experience running GPU workloads and/or deploying ML models to production