MLOps Engineer

Quick Facts

• Role: MLOps Engineer (Azure, AI platform / LLMOps)

• Work style: Hybrid (minimum 1 day/week in Warsaw)

Description

You will build and maintain an AI platform for the insurance industry, designing scalable MLOps/LLMOps infrastructure on Azure for training and serving models.

The role covers CI/CD/CT pipelines for ML (testing, data/model versioning), Docker image creation, Kubernetes-based deployments with hybrid on-prem integration, and production monitoring including drift detection.

You will also support AI Act compliance tooling (auditability, data lineage, access control, encryption) and optimize Azure cost and inference performance.

Responsibilities

• Create and maintain an AI platform for an insurance use case

• Design and build scalable MLOps/LLMOps infrastructure for training and serving models on Azure (e.g., Azure Machine Learning, Azure AI Foundry, AKS)

• Implement CI/CD/CT pipelines for ML including automated testing and data/model versioning (e.g., DVC, MLflow)

• Prepare Docker images for AI/GenAI models and deploy them to Kubernetes in a hybrid architecture integrating on-prem systems

• Implement model monitoring (data drift/model drift), logging, and alerting to ensure high availability

• Support AI Act compliance with auditability tools, data lineage, and security (access management, encryption)

• Optimize Azure costs and performance; scale infrastructure based on load

Requirements

• 3+ years of experience in DevOps/MLOps/software engineering, including hands-on ML model work in production

• Advanced Docker and Kubernetes skills (cluster management, Helm charts, Ingress)

• Strong Azure expertise (Azure ML, AKS, Azure Container Registry) or GCP/AWS experience with readiness to quickly move to Azure

• Experience building CI/CD pipelines for ML workloads using Azure DevOps, GitHub Actions, or Jenkins

• Proficient in Python and Bash/Shell

• Practical experience with MLflow, Kubeflow, or equivalent model lifecycle tooling

• Knowledge of Terraform, Bicep, or Ansible

• Technical higher education (CS/telecom or related)

• Automation-first mindset to eliminate manual work using scripts and tools

• Ability to collaborate across Data Science and IT Operations teams

• Proactive troubleshooting of performance issues and production incidents

• Ability to provide services from Poland

Benefits

• Work on an Azure-based AI platform using modern MLOps/LLMOps practices

• Hybrid work model with time in a Warsaw office

• Contribute to AI Act–oriented auditability and security capabilities