Machine Learning Engineer

Budget: 650-750 Context As part of an Employee Virtual Assistant initiative, the mission is to help turn a product vision into a coherent technical implementation roadmap. The role focuses on structuring and deploying Python micro‑services, ensuring clear service boundaries so multiple teams can work efficiently in parallel. You will also promote industrial engineering standards across the ML&AI community by enabling production‑ready ML pipelines and the integration, deployment, and monitoring of AI services in close collaboration with Data Scientists and IT Production. Responsibilities Structure the technical vision into a clear implementation roadmap for the employee virtual assistant Design and define micro‑service boundaries to enable parallel delivery across teams Develop, deploy, and maintain Python micro‑services for AI/ML services Work with Data Scientists to define target solutions with production constraints (e.g., data ingestion, API synchronicity, volumetry, real‑time needs) Contribute to ML pipeline automation for production integration and deployment (e.g., Docker/VM images, unit, regression and integration tests) Support Data Scientists in using existing industrial solutions for building and monitoring AI services (e.g., CI/CD tools) Support IT Production in target environment parameterization Contribute to monitoring, retraining (including automation where applicable), and ensuring models run reliably without errors Share knowledge and best practices within the chapter (Swagger, mocking, testing) Technical Skills Must have At least 6 years of relevant experience Proven experience building and deploying Python micro‑services Strong knowledge of: Containerization CI/CD Code, model & data versioning Cloud computing services Relational databases Swagger / schema definition AI platforms & IDEs Experience contributing to development, deployment, and monitoring of AI services (data quality checks, data flow design, model integration) Project coordination experience Strong communication skills (oral & written) Results‑driven mindset with high attention to detail and rigor Proactive continuous learning and knowledge sharing attitude English: mandatory Education: Master’s in Computer Science or related field/experience Should have Knowledge of mocking and testing practices (and willingness to coach others) Certifications in Linux, Python, and/or Data Science (a plus) Familiarity with ML packages and libraries relevant to the entity/project Ability to facilitate communication between AI & Analytics teams and IT Production regarding ML deployment Nice to have Dutch (nice to have) French (nice to have) Knowledge of the IT language of the entity/project (preferred) Experience with model compression techniques Who We Are Community Consulting goes beyond traditional consulting; it’s all about fostering connections in an atmosphere of trust and confidence. Transparency & Honesty : We say things as they are. Clear communication for seamless collaboration. #COMMUNITEAM : Work independently, but never alone. Collective intelligence drives us further, faster. Total Commitment : Always present, always engaged. We find solutions and make sure everyone moves forward together. Guaranteed Efficiency : No fluff, just results. We act fast, keep our promises, and deliver top quality. This is our DNA. This is how we make a difference. Type Permanent or Freelance Contract Full‑time Location Brussels Homeworking 2 days per week Sector Bank Keywords Python microservices ML pipelines CI/CD & MLOps You Career Advisor Lena VandecnockeLead Talent Management & Business Ops #J-18808-Ljbffr