R&D - AI Engineer (Mid)

Innovation Labs a leading R&D and Innovation company with the vision to leverage research in developing world-impacting solutions that bring value to society. Building on more than 30 years of applied research experience, we work at the intersection of artificial intelligence, data analytics, and large-scale software engineering to address complex challenges across multiple sectors. Our teams bring deep expertise in AI, machine learning, big data analytics, real-time and distributed systems, complex event processing, and cloud-native architectures. Drawing on strong foundations in European research and close collaboration with academic and industry partners, we are now channeling this experience into the development of scalable products. At Innovation Labs our people are at the core of everything we do. We foster a transparent, inclusive, and curious culture that values responsibility, continuous learning, and purposeful innovation. We are driven by the ambition to build technology that makes a meaningful difference. The Role You will join a multidisciplinary team of Engineers, Data Scientists and innovation management Experts that excel in driving innovation in software engineering, A.I and data analytics, to foster advances in key sectors such as: security, health, creativity and lifelong learning. You will participate in innovative research projects that strive for improving the quality of people’s lives and the efficiency of provided social services. You will create AI solutions to address both every-day problems for individuals and societal challenges. You will be exposed to fascinating domains like healthcare AI, autonomous systems, and more. You'll work alongside leading academics, industry pioneers, and AI experts, contributing to projects that shape the future of technology in Europe. You will attend workshops, and project meetings across Europe, expanding your professional network while experiencing diverse cultures. Main duties Define AI solutions & design its architecture (technical requirements definition, data requirements definition) Develop Machine Learning algorithms and techniques, building and maintaining end-to-end solutions Develop Generative AI and AI Agent solutions, including LLM-based applications, retrieval-augmented generation (RAG) systems and agentic workflows Conduct Statistical analysis and fine-tune using test results Collaborate with data scientists and software engineers to build and maintain data and model pipelines Participate in meetings to understand end user requirements and define the AI tech specifications Deliver reports describing the AI solution