What you will do
You will participate directly in the design and development of AI and data science solutions to meet operational and tactical needs. Your responsibilities include:
- Developing machine learning pipelines and ensuring their monitoring and maintenance
- Deploying AI models into production, primarily in on-premise environments
- Implementing best standards in programming and machine learning within your projects
- Conducting technology watch to stay current with the latest developments in MLOps and machine learning
- Designing end-to-end ML systems taking into account scalability, robustness, maintenance and hardware constraints
- Working with large structured and unstructured datasets
What we are looking for
You hold a master's degree or doctorate in computer science, AI or equivalent, with a minimum of three years of experience in data science, MLOps and machine learning.
Technical expertise:
- On-premise and cloud development: expertise in developing and deploying AI solutions on-premise and on cloud platforms (Azure, AWS, GCP)
- Three or more years of industry experience in ML, MLOps and big data with a focus on large-scale deployment
- Theoretical background and practical expertise in machine learning and deep learning
- Strong knowledge of relational and non-relational databases (SQL and NoSQL), including PostgreSQL, MySQL, Milvus, Neo4J
- Demonstrable experience in deploying ML models and expertise in MLOps
- Experience with containerisation and deployment using Docker and Kubernetes, as well as orchestration tools like Kubeflow
- Mastery of ML pipelines (Kubeflow, MLflow, SageMaker)
- Mastery of CI/CD implementation for ML models and associated code
- Experience with different data storage solutions (data lakes, data warehouses, object storage such as S3)
Hard skills:
- Databases: MySQL, PostgreSQL, Neo4j, Milvus
- AI frameworks: Hugging Face, MLflow, PyTorch, TensorFlow, scikit-learn, OpenCV, vLLM
- Programming languages: Python (R is a plus)
- Orchestration and containerisation: Docker, Kubernetes, Kubeflow
- Software engineering: uv, ruff, black
- Cloud platforms: Azure, AWS
- Versioning (code and models): MLflow, Git, GitHub, GitLab
Soft skills:
- Ability to bring people together: aligning diverse profiles around a common objective
- Sense of priorities: identifying critical tasks, maintaining a long-term vision, and reorganising work in response to unexpected developments
- Clear and spontaneous communication: transmitting the right message at the right time and level, explaining technical concepts to non-technical stakeholders
- Problem-solving and analytical thinking: approaching problems in a structured way, identifying root causes and proposing pragmatic solutions
- Collaboration: working constructively with all stakeholders, fostering exchanges and co-construction of solutions
- Attention to detail: focusing on technical, functional and organisational aspects of projects, ensuring code quality, model robustness and compliance with standards
- Rigour: systematically applying best practices and methodologies, documenting work precisely, and ensuring consistent project follow-up
An awareness of security, ethical and legal aspects is appreciated.
The setting
This is a three-month freelance assignment starting in October 2026, based in Brussels with a hybrid working arrangement.
You must have active knowledge of English and at least one of the two national languages (Dutch or French).