MLOps Engineer

We are looking for an experienced MLOps Engineer to strengthen the team responsible for building scalable, stable, and fully automated ML environments on Azure. If you enjoy combining data engineering, automation, DevOps, and model architecture, this role will be a great fit for you.

🧩 RESPONSIBILITIES

• Designing and implementing end-to-end MLOps pipelines on Azure using Azure ML, AKS, ACR, and Azure Data Lake

• Containerizing and orchestrating ML workloads with Docker and Kubernetes, building scalable and resilient environments

• Automating model training, validation, and deployment through CI/CD pipelines integrated with Git and orchestration tools (Airflow, MLflow, Kubeflow)

• Managing model versioning, experiment tracking, and model registries (Azure ML Model Registry or equivalents)

• Implementing monitoring and alerting for model drift, data quality, and inference performance

• Creating and maintaining Infrastructure as Code (IaC) using Terraform, Bicep, or ARM Templates

• Applying security and compliance best practices for models, APIs, and data

🎯 IDEAL CANDIDATE

• Strong hands-on experience with Azure ML, AKS, Docker, Kubernetes, and production ML environments

• Proven experience building ML pipelines and CI/CD workflows, including integration with MLflow / Kubeflow

• Solid knowledge of Infrastructure as Code (Terraform / Bicep / ARM)

• Strong engineering mindset with a focus on automation, repeatability, and quality

• Good understanding of MLOps practices: model lifecycle, versioning, monitoring, and drift detection

✨ WHAT WE OFFER

• Real influence over the architecture of the ML environment

• Access to a modern Azure-based technology stack

• Stable, long-term cooperation on a strategic project

• Agile, highly skilled team with fast decision-making processes

• Ongoing support from the TQLO team throughout the collaboration

TQLO Sp. z o.o. — Employment Agency (KRAZ No. 33580)