Engineer H/F: Post-Training Generative Models for Education at Scale

Le descriptif de l’offre ci-dessous est en Anglais

Type de contrat : CDD

Niveau de diplôme exigé : Bac + 5 ou équivalent

Fonction : Ingénieur scientifique contractuel

Niveau d'expérience souhaité : Jeune diplômé

Contexte et atouts du poste

The 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.

Mission confiée

Design, implement, and evaluate generative AI systems for automated creation of pedagogically compliant educational exercises and content

Develop and optimize agentic architectures integrating large language models with structured ITS frameworks, ensuring pedagogical alignment and computational efficiency

Implement and fine-tune small-scale generative models for student learning trajectory prediction and personalized curriculum adaptation

Deploy LLM-as-judge frameworks and reinforcement learning approaches to evaluate and improve pedagogical quality of AI-generated content

Conduct large-scale experiments analyzing learning traces and student interactions with hybrid AI systems in authentic classroom environments

Collaborate with pedagogical experts, cognitive scientists, and industrial partners to translate educational requirements into technical specifications

Contribute to open-source software development and documentation for digital commons dissemination

Participate in scientific valorization through publications, presentations, and technical reports

Principales activités

Full description: https://www.pyoudeyer.com/researchEngineerGAIMHE26.pdf

Compétences

Required Profile and Expertise

Essential qualifications:

Advanced degree (Master's or PhD) in Computer Science, AI, Machine Learning, or related field

Demonstrated 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 models

Experience with agentic architectures, LLM orchestration, and prompt engineering

Knowledge of LLM-as-judge methodologies and/or reinforcement learning for LLMs

Strong programming skills (Python required, other languages valued)

Sufficient mastery of French language for collaboration with French educational partners and documentation

Ability to work collaboratively in interdisciplinary research teams

Valued qualifications:

Experience with learning analytics, educational data mining, or education research

Knowledge of cognitive science, learning theories, or pedagogical design principles

Familiarity with ITS architectures or adaptive learning systems

Experience deploying ML systems in production environments

Contributions to open-source projects

Publications in relevant AI, ML, or educational technology venues

Position details: Location: Inria Bordeaux - Sud-Ouest, Talence, France

Contract type: Fixed-term research engineer position Starting date: As soon as possible

To apply: Send CV, cover letter, and relevant portfolio/GitHub links to pierre-yves.oudeyer@inria.fr with [application] in the subject line.

Avantages

Subsidized meals

Partial reimbursement of public transport costs

Possibility of teleworking and flexible organization of working hours

Professional equipment available (videoconferencing, loan of computer equipment, etc.)

Social, cultural and sports events and activities

Access to vocational training

Social security coverage

Rémunération

From €2,692 gross per month before taxs - According to professional experience

Informations générales

Thème/Domaine : Robotique et environnements intelligents

Statistiques (Big data) (BAP E)

Ville : Talence

Centre Inria : Centre Inria de l'université de Bordeaux

Date de prise de fonction souhaitée : 2026-10-01

Durée de contrat : 2 ans

Date limite pour postuler : 2026-08-23

Attention: Les candidatures doivent être déposées en ligne sur le site Inria. Le traitement des candidatures adressées par d'autres canaux n'est pas garanti.

Consignes pour postuler

Please send:

CV

Cover letter

Your most recent qualification

Any letters of recommendation

Sécurité défense :

Ce poste est susceptible d’être affecté dans une zone à régime restrictif (ZRR), telle que définie dans le décret n°2011-1425 relatif à la protection du potentiel scientifique et technique de la nation (PPST). L’autorisation d’accès à une zone est délivrée par le chef d’établissement, après avis ministériel favorable, tel que défini dans l’arrêté du 03 juillet 2012, relatif à la PPST. Un avis ministériel défavorable pour un poste affecté dans une ZRR aurait pour conséquence l’annulation du recrutement.

Politique de recrutement :

Dans le cadre de sa politique diversité, tous les postes Inria sont accessibles aux personnes en situation de handicap.

Contacts

Équipe Inria : FLOWERS

Recruteur :

Oudeyer Pierre-yves / Pierre-Yves.Oudeyer@inria.fr

A propos d'Inria