Azure ML Engineer

Mission opportunity · Hybrid

Client: Belgian public organisation (IT department of 150+ people)
Work regime: Hybrid, 2 days office, 3 days teleworking
Languages: French or Dutch (native or excellent), good understanding of the second national language

Context

As part of its digital transformation, our client aims to deploy machine learning solutions to optimise processes, support decision-making and strengthen digital services, with a focus on reliable, scalable and maintainable ML solutions integrated into existing systems, both in Azure and on-premise.

Main mission

As ML Engineer, you design, build, deploy and maintain machine learning models and ML pipelines. Your role sits at the intersection of data, software engineering and MLOps, with a clear focus on robust implementation, reproducibility, monitoring and compliance with regulations such as the European AI Act.

Key responsibilities

• Data preparation & feature engineering: process, analyse and prepare data; ensure quality and consistency within ML workflows.
• Model development & validation: design, train and tune models (classification, forecasting, detection) with clear validation criteria.
• Operationalisation: turn models into production-ready services, APIs or batch processes.
• MLOps & reliability: CI/CD, monitoring of performance, latency, data and model drift, retraining mechanisms.
• Collaboration: align with developers, data engineers and architects; document and share knowledge.

Required skills

• MLOps & pipelines: strong experience with ML pipelines and CI/CD.
• Cloud & infrastructure: Azure as well as on-premise systems.
• Engineering: code versioning, configuration management, integration of models into production services.
• Compliance: knowledge of best practices and of the European AI Act.

Nice to have

• Agile: experience with SAFe.
• Teamwork: multi-disciplinary teams with data engineers and architects.