MLOps Engineer

Your tasks

We are looking for an Operations Engineer with a solid background in Data Science and Machine Learning to support our mature, fully deployed production algorithms. This role focuses on long-term operational stability, system health, and minor maintenance rather than developing new solutions from scratch.

The environment is highly stable with a low incident volume (typically around one incident per month). You will act as the dedicated technical expert for these production models, collaborating closely the internal product, architecture, and platform teams.

• Monitor algorithm health, performance, and general operational workflows for deployed machine learning and optimization solutions.
• Investigate, troubleshoot, and resolve production incidents within the European time zone to meet defined SLA targets (ownership and closure).
• Perform minor enhancements, maintenance tasks, and support occasional production deployments or periodic model refreshes.
• Maintain deep, model-specific knowledge to perform deeper technical investigations and refreshes when required.

Requirements

• Practical experience with Microsoft Azure tools, specifically Azure Data Factory, Databricks, Azure ML.
• Familiarity with GitHub / Azure DevOps for version control and deployment pipelines.
• Experience with Power BI for reporting and ServiceNow (or similar ticketing systems) for incident tracking.
• Understanding of Machine Learning or mathematical optimization workflows from an operational support perspective.
• Experience working within defined SLA frameworks in a production environment.

Must have:

• Python
• Azure
• Azure Data Factory
• Docker