MLOps Engineer

Описание The client is developing a modern claims and benefits handling ecosystem based on data, automation, AI, and workflow processes as part of a strategic business and technology transformation program.

Задачи • Implement CI/CD pipelines for ML solutions, including automated testing, data and model versioning, and Continuous Training • Design and build scalable MLOps/LLMOps infrastructure for model training and serving using Azure Machine Learning, Azure AI Foundry, and Kubernetes (AKS) • Prepare Docker images for AI/GenAI models and manage deployments on Kubernetes clusters in a hybrid architecture integrated with on-premise systems • Manage Azure cloud resources, optimize model inference time, and scale infrastructure based on workload

Требования • At least 3 years of experience in MLOps, Machine Learning, or Data Engineering • Deep knowledge of Azure, especially Azure ML, AKS, and Azure Container Registry, or GCP/AWS with readiness to quickly ramp up on Azure • Hands-on experience with MLflow, Kubeflow, or cloud-native solutions for model lifecycle management • Advanced knowledge of Docker and Kubernetes, including cluster management, Helm charts, and Ingress • Experience building pipelines with Azure DevOps, GitHub Actions, or Jenkins • Good knowledge of Python and Bash/Shell • Knowledge of Terraform, Bicep, or Ansible • Будет плюсом: Charts, Ingress, GCP, AWS, GitHub Actions, Jenkins, Shell, Ansible, Bicep, LLM, RAG, Prometheus, Grafana, Azure Monitor

Условия •…