Research Engineer (Trustworthy AI)
Pubblicato il 27-09-2026 - Generali Group in Trieste
Within the Agorai Innovation Hub we are looking for a talented and proactive resource, who will work directly with the AI Architect and Head of Technology on use case definition and technical direction.The researcher will work at the intersection of language understanding, knowledge representation, and trustworthy AI. This means combining LLMs with structured knowledge to ground reasoning; designing evaluation frameworks that surface failure modes before they reach production; and building information extraction systems whose outputs can be audited.Key responsibilities of the role will include:Own the research-to-production arc on language understanding and knowledge-grounded AI: from literature review and experimentation to deployment and monitoringDesign AI systems whose outputs can be explained, audited, and trusted in regulated contexts — and know when simpler approaches serve that goal better than complex onesBuild production-quality services around your models: APIs, inference pipelines, evaluation harnessesDesign evaluation frameworks that go beyond benchmark metrics — testing for failure modes, edge cases, and behavior under distribution shiftWork on information extraction, semantic understanding, and structured knowledge problems grounded in real industrial dataStay current with the research frontier in language models, interpretability, and trustworthy AIContribute to technical standards and code quality across the teamWork on a genuinely hard and open research problem with direct industrial applicationThe role is based in Trieste and includes a hybrid work model, offering flexibility through remote working days.Master's degree or PhD in Computer Science, Artificial Intelligence, Data Science, Engineering or a related STEM fieldAt least 3–5 years of experience working with NLP or language understanding systems in production environments, such as text classification, information extraction, semantic search, RAG, or generative systemsAt least 3–5 years of experience in applied NLP or computer vision,
working with real-world data and operational constraints rather than benchmark-only environmentsExperience working across one or more of the following sectors: Healthcare, Financial Services, Mobility/Transport, AgricultureTechnical SkillsFluent across the stack: LLM-based systems, classical ML, APIs, microservices, inference optimizationStrong software engineering fundamentals: your code is modular, testable, and maintainable by someone other than youComfort with the full arc from prototype to production: you know what a model registry is, you have thought about inference latency, you have monitored a deployed modelWorking knowledge of Python ML ecosystem: PyTorch or JAX, HuggingFace, experiment tracking (MLflow, W&B;), serving frameworksSoft Skills & Personal AttributesEntrepreneurial mindset: takes ownership, operates with autonomy and drives things forward without waiting for directionGenuine interest in trustworthy and explainable AI — not as a theoretical topic but as a design constraint that shapes how you buildExcellent communication and stakeholder management skills; able to interact effectively with both technical teams and C-suite executives or institutional clientsLanguagesEnglish: Full professional proficiency required (primary working language for international projects and publications)Italian: Knowledge of Italian is considered an advantageWhat we offerWe offer employment at the VI Professional level with the relevant salary, in accordance with the CCNL ANIA for non-executive employees and the Generali Group Company Agreement.Gross annual salary starting from 50K. The final offer will be aligned with the candidate’s professional experience, technical and soft skills relevant to the role, and may include an individual variable component.We also offer:Lavoro da remoto and flexible hoursCorporate welfare systemMeal vouchersSupplementary health insurance and discounted insurance policiesWellbeing initiativesTraining and developmentStructured continuous learning paths (technical and managerial)Career development programsAccess to learning platforms and internal mobility opportunities