AI Engineer
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Job description
Our client currently has a vacancy for an AI Engineer fluent in English, to offer his/her services as an expert who will be based in Brussels, Belgium. The work will be carried out either in the companys premises or on site at customer premises. In the context of the first assignment, the successful candidate will be integrated in the Development team of the company that will closely cooperate with a major clients IT team on site., * Development and maintenance of AI solutions, defined as software applications that integrate AI (Natural Language Processing, Machine Learning, Generative AI);
- Design and implement of IT architecture for AI solutions under expert understanding of most appropriate AI components, techniques and models, applying modern AI approaches, as well as modern IT architecture practices;
- Present AI solutions blueprints to technical and business audiences. Moderate discussions and collect relevant technical and business feedback;
- Support implementation of best practices for data, master- and metadata management and modern MLOps;
- Training of custom machine learning and deep learning models (including transformer-based architectures) based on structured and unstructured data.
Requirements
- Masters degree in IT or relevant discipline, combined with minimum 9 years of relevant working experience in IT;
- Excellent knowledge of Python and its core AI/ML/NLP libraries and frameworks (e.g., pandas, OpenAI, spaCy, PyTorch, TensorFlow, Transformers, scikit-learn, NLTK);
- Proven experience with advanced AI/ML techniques including LLMs, generative AI architectures, RAG, agentic workflows (OpenAI, LangChain, CrewAI), function calling, MCP, and traditional machine learning algorithms in production environments;
- Strong experience with modern data management and engineering techniques, including data pipelines, metadata/model versioning, and database integration (relational SQL and NoSQL solutions like Elasticsearch, MongoDB, Cassandra);
- Strong experience with cloud computing platforms (AWS, Azure) for deploying, scaling, and securing AI solutions;
- Practical knowledge of modern software engineering and DevOps practices including Git workflows, CI/CD pipelines, containerization (Docker, Kubernetes), and agile methodologies;
- Demonstrated ability to independently develop, test, document, and integrate AI/ML components as part of larger service-oriented architectures;
- Experience with ethical/legal implications of AI systems in enterprise or public sector environments would be a great asset.
- Excellent command of the English language.
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