Senior MLOPS Engineer

<p></p><h2>Your benefits</h2><p><strong></strong></p><ul> <ul> <li><strong>Corporate Benefits:</strong> You will receive a best-in-class benefits package including, for example, an electric lease car or mobility budget, laptop &amp; mobile phone, work from home budget, 25 holidays + optional to buy 5 days extra a year and pension contributions.</li> <li><strong>Flexible Working:</strong> Your plans are as unique as you are. Choose your place of work flexibly – whether in one of our office locations or remotely.</li> <li><strong>Mentorship:</strong> Experienced colleagues will support you during your start and development.</li> <li><strong>Personal Development:</strong> Look forward to responsible tasks with a high degree of creative freedom, a steep learning curve, and an extensive range of training courses.</li> <li><strong>Team Spirit:</strong> We embrace flat hierarchies and a team-oriented corporate culture. Ecological responsibility and social commitment are part of our DNA.</li> <li><strong>Remuneration Model:</strong> Benefit from our attractive model, including a performance-related bonus.</li> <li><strong>Work-Life Balance:</strong> We offer a wide range of options, including sabbaticals and workations.</li> </ul></ul><p></p><p></p><h2>Your future tasks</h2><p>As a <strong>Senior </strong><strong>MLOps Engineer</strong>, you will be part of our <strong>Data &amp; Analytics service line</strong>, operating as a unified team across BearingPoint NL. Within this service line (team), we define three streams of thought: Data Management &amp; Strategy, Data Engineering and Data Insights and Analytics. Our team aims to support clients in their end-to-end data and analytics needs, ranging from data strategy and data management to predictive and prescriptive analytics. </p><p></p><p>As a <strong>Senior </strong><strong>MLOps Engineer</strong>, you will design and implement robust, scalable MLOps solutions that bridge the gap between data science and production environments. You will advise clients on how to operationalize machine learning models effectively and sustainably, ensuring they deliver long-term value. </p><p></p><p>You will: </p><ul> <li><strong>Lead </strong><strong>MLOps implementations</strong>: design and build end-to-end MLOps pipelines, establish CI/CD practices for Machine Learning models, and automate deployment processes to ensure scalable and reliable Machine Learning systems in complex enterprise environments. </li> </ul><ul> <li><strong>Drive </strong><strong>innovation and thought leadership</strong>: stay ahead of developments in MLOps, model governance, responsible AI, and GenAI. Promote best practices and lead the adoption of modern ML infrastructures across client organizations. </li> </ul><ul> <li><strong>Mentor and </strong><strong>guide teams</strong>: manage initiatives and coach junior engineers in building production-ready ML systems. Facilitate knowledge sharing, lead model governance discussions, and develop innovative solutions to complex ML deployment challenges. </li> </ul><ul> <li><strong>Support Client Development</strong>: shape ML infrastructure strategies and architect scalable platforms that enable AI transformations. Your technical leadership and operational insights will help deliver robust and future-proof solutions. </li> </ul><p><br/></p><h2><br/></h2><h2>Your profile</h2><ul> <li>A relevant and completed Master of Science degree including certifications in cloud platforms (Azure and/or AWS).</li> <li>6–8 years of experience in DevOps, ML engineering, or software engineering with a focus on ML. Preferably in a consulting environment.</li> <li>Extensive hands-on experience with MLOps tools and platforms including strong programming skills in Python and experience with ML frameworks (e.g., TensorFlow, PyTorch, scikit-learn, XGBoost).</li> <li>Deep expertise in containerization and orchestration technologies for ML workloads. And experience with cloud-native ML services and serverless computing for ML workloads.</li> <li>Experience with Infrastructure as Code (IaC), stream processing, real-time ML inference architecture, model monitoring, drift detection, and ML observability tools. </li> <li>Understanding of ML security, testing strategies, model governance, and responsible AI practices. And knowledge of feature stores, model registries, data- and model versioning, and experiment tracking systems.</li> <li>Good communication and presentation skills in both Dutch and English.</li> </ul><p><br/></p><ul> </ul><p></p><ul> </ul><p></p><h2>Together, we are more than Business</h2><p>BearingPoint is an independent management and technology consultancy with European roots and global reach. We offer consulting that combines strategy with technology and combine entrepreneurship with a spirit of innovation.<br/>You make the difference: We give you the space to be yourself and develop your full potential. Regardless of where you come from, what you believe in or who you lo