Engineer F/H: Generative AI agentic architectures for educational technologies

Engineer F/H: Generative AI agentic architectures for educational technologiesThe Flowers AI & CogSci Lab at Inria, in partnership with EvidenceB, Café pédagogique, and ClassCode, is launching GAIMHE (Generative AI for Hybrid Mathematics Education), a large-scale research and innovation project funded by Bpifrance. This initiative addresses a critical challenge in educational technology: developing AI systems that combine the pedagogical rigor and personalization capabilities of Intelligent Tutoring Systems (ITS) with the flexibility and generative power of modern large language models.Current ITS platforms, such as EvidenceB's AdaptivMaths, leverage cognitive science principles and structured pedagogical graphs to deliver personalized learning pathways to students. These systems have demonstrated effectiveness across tens of thousands of classrooms in France (primary, middle, and high schools, across multiple disciplines including AdaptivMaths and MIA Seconde). However, their development requires substantial manual content creation. Conversely, generative AI offers unprecedented flexibility but often lacks pedagogical grounding, cannot sustain long-term curriculum personalization, and raises concerns about energy efficiency and pedagogical biases.GAIMHE will develop hybrid architectures that harness generative AI for automated content generation while maintaining pedagogical constraints, deploy targeted generative guidance aligned with established learning theories, and create compact student models for next-generation personalization algorithms. The project will leverage EvidenceB's extensive deployment infrastructure to work with authentic large-scale educational data and validate innovations in real classroom settings. In alignment with open science principles and through partnership with Région Île-de-France, major project outputs (datasets, models, software) will be released as digital commons under open-source licenses.Design, implement, and evaluate generative AI systems for automated creation of pedagogically compliant educational exercises and contentDevelop and optimize agentic architectures integrating large language models with structured ITS frameworks, ensuring pedagogical alignment and computational efficiencyImplement and fine-tune small-scale generative models for student learning trajectory prediction and personalized curriculum adaptationDeploy LLM-as-judge frameworks and reinforcement learning approaches to evaluate and improve pedagogical quality of AI-generated contentConduct large-scale experiments analyzing learning traces and student interactions with hybrid AI systems in authentic classroom environmentsCollaborate with pedagogical experts, cognitive scientists, and industrial partners to translate educational requirements into technical specificationsContribute to open-source software development and documentation for digital commons disseminationParticipate in scientific valorization through publications, presentations, and technical reportsRequired Profile and ExpertiseAdvanced degree (Master's or PhD) in Computer Science, AI, Machine Learning, or related fieldDemonstrated expertise in large-scale generative AI systems (inference and training pipelines)Strong experience with modern deep learning frameworks (PyTorch, TensorFlow, Hugging Face ecosystem)Proficiency in training and optimizing small-to-medium scale language modelsExperience with agentic architectures, LLM orchestration, and prompt engineeringKnowledge of LLM-as-judge methodologies and/or reinforcement learning for LLMsStrong programming skills (Python required, other languages valued)Sufficient mastery of French language for collaboration with French educational partners and documentationAbility to work collaboratively in interdisciplinary research teamsExperience with learning analytics, educational data mining, or education researchKnowledge of cognitive science, learning theories, or pedagogical design principlesFamiliarity with ITS architectures or adaptive learning systemsExperience deploying ML systems in production environmentsContributions to open-source projectsPublications in relevant AI, ML, or educational technology venuesPosition details: Location: Inria Bordeaux - Sud-Ouest, Talence, FranceContract type: Fixed-term research engineer position Starting date: As soon as possibleTo apply: Send CV, cover letter, and relevant portfolio/GitHub links to pierre-yves.oudeyer@inria.frwith [application] in the subject line.AvantagesPartial reimbursement of public transport costsPossibility of teleworking and flexible organization of working hoursProfessional equipment available (videoconferencing, loan of computer equipment, etc.)Social, cultural and sports events and activities #J-18808-Ljbffr