Senior Data Scientist - GenAI

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Join Artefact Belgium: Lead the Future of Generative AI and Large Language Models

Are you a seasoned AI professional with a passion for generative AI and Large Language Models (LLMs)? Artefact Belgium is looking for a Senior Data Scientist - Gen AI to drive innovation and lead cutting-edge projects. If you have at least four years of experience in AI and consulting, combined with a talent for project and team management, we invite you to shape the future of LLM-driven solutions with us in Brussels.

Who You Are

• Experienced professional: At least 4 years of experience in AI, with a strong background in consulting and delivering impactful projects for diverse clients.

• Leader and collaborator: Proven experience managing teams, guiding junior colleagues, and fostering collaboration in multidisciplinary environments.

• Innovative thinker: Able to identify emerging trends in generative AI and apply them to real-world challenges.

• Results-oriented: Comfortable handling end-to-end project delivery, from ideation and development to deployment and client engagement.

• Eager to grow: Passionate about advancing your expertise in LLMs and generative AI while mentoring others.

Who We Are

Artefact is a leading Data & AI consulting firm at the forefront of AI innovation. With a global presence, we collaborate with top-tier clients across industries, including healthcare, manufacturing, and media, to harness the transformative power of generative AI. Our team in Belgium is specialized in LLM and GenAI projects, working on the most advanced applications of these technologies. Our inclusive and forward-thinking culture encourages creativity, collaboration, and professional growth.

What You Will Do

• Lead and deliver LLM projects: Manage the design, development, and deployment of advanced LLM-powered solutions, including RAG systems, agentic AI architectures, and multi-modal applications for our clients.

• Drive technical excellence: Architect and deploy advanced AI systems leveraging cutting-edge techniques such as parameter-efficient fine-tuning (LoRA/QLoRA), prompt orchestration, retrieval-augmented generation (RAG), function/tool calling, multi-agent workflows, and emerging interoperability standards like the Model Context Protocol (MCP).