mlops engineer in insurance services

The client is a leader in insurance services in Poland, specializing mainly in property and personal insurance. It also handles debt collection and supports customers in repaying financial obligations, while developing its systems and applying modern IT solutions.

• Build and maintain an AI platform in the insurance industry
• Design and build scalable MLOps/LLMOps infrastructure for training and serving models using Azure Machine Learning, Azure AI Foundry, and Kubernetes (AKS)
• Automate CI/CD/CT processes for ML solutions, including testing, data and model versioning, and Continuous Training
• Prepare Docker images for AI/GenAI models and manage deployments on Kubernetes clusters in a hybrid architecture integrated with on-premise systems
• Implement model monitoring, Data Drift/Model Drift detection, logging, and alerting to ensure high availability of AI services
• Implement tools for model auditability, lineage, and security in line with regulatory requirements
• Manage Azure cloud resources, optimize model inference time, and scale infrastructure based on load

• At least 3 years of experience in DevOps, MLOps, or Software Engineering, including practical experience with ML models in production
• Advanced knowledge of Docker and Kubernetes, including cluster management, Helm charts, and Ingress
• In-depth knowledge of Azure, especially Azure ML, AKS, and Azure Container Registry, or GCP/AWS experience and readiness to move to Azure quickly
• Experience building CI/CD pipelines with Azure DevOps, GitHub Actions, or Jenkins, accounting for ML-specific requirements such as model training as a pipeline step
• Good knowledge of Python and Bash/Shell
• Practical experience with MLflow, Kubeflow, or cloud-native tools for managing the model lifecycle
• Knowledge of Terraform, Bicep, or Ansible
• Services must be provided from Poland
• Services must be provided in a hybrid model, with at least 1 day per week in the office
• Будет плюсом: Azure DevOps Engineer Expert (AZ-400) or Azure AI Engineer (AI-102) certifications, experience deploying LLMs and RAG architectures, knowledge of Prometheus, Grafana, or Azure Monitor, understanding of hybrid cloud networking (VPN, VNet, Private Endpoints), knowledge of vector databases such as Azure AI Search

• Rate: 150 - 170 PLN net + VAT/h