Also available on
Job Description
📋 Description Empower ML Engineers with tools, infra, and frameworks to iterate fast. Accelerate time-to-market for production ML products with seamless integration. Own ML CI/CD with ML team, adapting frameworks to ML needs. Keep models under production control: monitor, troubleshoot, iterate in prod. Enable large-scale ML experimentation with robust, scalable prod environments. Deliver MLOps building blocks (MLflow, Kubeflow, KubeRay) and GPU infra. 🎯 Requirements Solid MLOps or DevOps; production experience matters most. GCP expert: Vertex AI, GKE, GCS, BigQuery. Full GitOps: FluxCD first, ArgoCD accepted. Kubernetes in prod, not just lab. Hands-on with ML tools: MLflow, Kubeflow, KubeRay. GPU-aware: manage GPU scarcity at scale during training.
