Job Type: Permanent / Full-TimeWorking Hours: 36–40 hours per weekWork Location: Brussels, BelgiumWorking Model: Hybrid (50% on-site, 50% remote)Experience Level: Experienced Professional
Role OverviewMachine Learning Engineers promote the adoption of best standards in industrial code development across the ML&AI community. They do so by developing ML pipelines that are production-ready by design or by integrating existing ML solutions into industrial pipelines.
They participate in the development, deployment and monitoring of AI services, which means they contribute to data quality checks, data flow design, the design of the models themselves and their overall integration into the production environment.ML Engineers are meant to facilitate the communication between AI & Analytics teams and IT production with regards to the deployment of ML models, ensuring that models put in production are equipped with the appropriate data pipelines and monitoring.
Key ResponsibilitiesAs a Machine Learning Engineer, you will:Collaborate with Data Scientists to design and develop ML solutions with production constraints in mind.Select appropriate infrastructure, serving models, and data ingestion approaches to meet business requirements such as real-time processing and high data volumes.Automate and industrialize end-to-end ML pipelines, including:Docker/VM image creationUnit, regression, and integration testingContinuous integration and deploymentSupport Data Scientists in using existing industrial AI platforms and CI/CD tools for building and monitoring AI services.Work closely with IT Production teams to configure and optimize target production environments.Participate in the deployment, monitoring, and maintenance of AI/ML services.Ensure proper data quality checks, data flow design, and model integration within production systems.
Mandatory Skills & ExperienceMinimum 4 years of relevant experience as an ML Engineer or related roleStrong experience in Python (advanced level)Experience with containerization and virtualization technologiesHands-on experience with AI platforms and IDEsCI/CD pipelines (especially GitLab CI)Code, model, and data versioningPackage management tools and dependency managementDatabase experience with PostgreSQLSolid understanding of Agile methodologies
Preferred / Nice‐to‐Have SkillsExperience with system integration across distributed systems, mainframe, and infrastructure componentsKnowledge of model compression techniquesExperience with ELT / ETL toolsExposure to Big Data technologies (e.g., Apache Spark)Knowledge of data flow / stream processingFamiliarity with data visualization tools
Soft SkillsStrong verbal and written communication skillsResult‐oriented and delivery‐focused mindsetAttention to detail and strong analytical rigorCreativity, innovation, and problem‐solving abilityProactive approach to continuous learning and skill developmentAwareness of efficiency and effectivenessAbility to think outside existing processes and frameworksPositive energy, ownership mindset, and strong collaboration skillsOpen to change, feedback, and diverse viewpoints
Your home at CapgeminiYou will join Capgemini Financial Services Benelux, working alongside passionate and skilled colleagues toward shared goals. Capgemini offers:Structured onboarding and transparent growth pathsFlexibility to shape your own career journeyA culture of trust, collaboration, and innovationOpportunities to work at the international forefront of technologyStrong commitment to sustainability, diversity, and inclusion
Working at CapgeminiGet the future you want. That's a promise we make to you. It starts on day one. With good onboarding and structured and transparent growth paths. But also: plenty of opportunities to deviate from these to pioneer and to choose your own path. You can count on our boundless trust and collegial support. Working for Capgemini also means working in the international heart of innovation. The premier league of technology. An employer with an eye for you and a sight on the future, in which sustainability and diversity and inclusion play the main roles.