Senior MLOps Engineer

<p>At <strong>Telenet</strong>, we’re on a mission to weave machine learning and AI into every part of our operations, decisions, and customer experiences. To make this vision a reality, we’re expanding our <strong>MLOps team</strong> — the bridge between brilliant data science and tangible business impact.</p> <p>With over <strong>50 data experts</strong> (Data Scientists, Data Engineers, Data Strategists, CRM Experts, and of course dedicated MLOps Engineers), a cutting-edge <strong>AWS Cloud</strong> setup, and strong collaboration with business teams, our Predictive AI Cluster already drives major value: from predicting faulty customer equipment and optimizing network investments to enabling hyper-personalized communication.<br/> Now, we’re looking for a <strong>Senior MLOps Engineer</strong> to take the lead in turning ML models into scalable, reliable production systems.</p> <p><strong>Your tasks a Senior MLOps Engineer</strong></p> <p>As Senior MLOps Engineer, you’ll be the technical lead of our MLOps operations, building automation, ensuring reliability, and mentoring others. You’ll design, deploy, and maintain a <strong>robust</strong> <strong>MLOps ecosystem</strong> for both batch and online inference.</p> <p><strong>Key responsibilities:</strong></p> <ul> <li>Ensure <strong>reliable delivery of model outputs</strong> to business and system users</li> <li>Automate deployment and scoring pipelines (<strong>CI/CD</strong>, <strong>orchestration</strong> via Dagster/Airflow)</li> <li>Monitor production ML workloads for <strong>performance, data quality, and model drift</strong></li> <li>Maintain and evolve our shared <strong>MLOps framework</strong> and reusable templates</li> <li>Manage, maintain and improve the central <strong>AI Feature Store</strong>.</li> <li>Build reusable components to <strong>accelerate model lifecycle</strong> (deployment, validation, packaging)</li> <li>Coach junior MLOps Engineers and champion <strong>MLOps best practices</strong>.</li> </ul> <p><strong>What we offer</strong></p> <ul> <li>Start a new adventure in an innovative, healthy and ambitious organization that aims to become an (inter)national frontrunner in leveraging AI and machine learning.</li> <li>Enjoy flexible working hours and the freedom to work from home (3 days per week) or in our open and trendy collaboration spots at the office.</li> <li>Work in a state-of-the-art AWS Cloud environment.</li> <li>We’ll coach you, train you and make you part of our story. You’ll have access to an extensive training catalogue and external platforms such as DataCamp and Linkedin Learning, and ample opportunity to learn on the job.</li> <li>An agile organization that encourages personal growth, internal mobility and the possibility to change roles.</li> <li>Join a team of young, dynamic, enthusiastic and results-driven data professionals, with fun team buildings, on-site padel games and the occasional afterwork drinks.</li> <li>Enjoy an attractive compensation &amp; benefits package, including a mobility budget, meal vouchers, group and health insurance, a yearly bonus and discounts on Telenet products.<br/>  </li> </ul> <p><strong>Our ideal Senior MLOps Engineer</strong></p> <p>You connect the worlds of data science and engineering with a focus on quality, scalability, and automation.</p> <ul> <li>4+ years in Data Science and Data Engineering, including 1+ year focused on MLOps.</li> <li>Solid skills in <strong>Python, PySpark, and SQL</strong>, with experience in ML/data libraries (pandas, scikit-learn, PyTorch).</li> <li>Hands-on experience with <strong>Git, CI/CD</strong>, and workflow orchestration tools.</li> <li>Experience deploying workloads in <strong>AWS</strong> (SageMaker a plus).</li> <li>Familiarity with <strong>Snowflake</strong> and/or <strong>dbt</strong> is a bonus.</li> <li>Strong ownership mindset, autonomy, structured thinking, and operational discipline.</li> <li>Fluent English and a drive to learn continuously.</li> </ul>