General information
Organisation
The French Alternative Energies and Atomic Energy Commission (CEA) is a key player in research, development and innovation in four main areas :
• defence and security,
• nuclear energy (fission and fusion),
• technological research for industry,
• fundamental research in the physical sciences and life sciences.
Drawing on its widely acknowledged expertise, and thanks to its 16000 technicians, engineers, researchers and staff, the CEA actively participates in collaborative projects with a large number of academic and industrial partners.
The CEA is established in ten centers spread throughout France
Reference
2026-42011
Description de l'unité
Within the Institute and the Department of Ambient Intelligence and Interactive Systems (DIASI), and the Artificial Intelligence, Language, and Vision Service (SIALV), the Laboratory for Semantic Analysis of Text and Image (LASTI) conducts foundational research projects in artificial intelligence applied to computer vision, automated processing, and multimodal data analysis.
The global acceleration of AI research has made the field extremely competitive. To maintain its scientific excellence and technological competitiveness, LASTI—in partnership with other laboratories within the service—aims to expand its capacity for developing and operationally implementing AI-based systems. The design process for AI models requires a high level of proficiency in software environments that facilitate the handling of data, annotations, and models, as well as their integration into complex systems across various computational scales (ranging from the training and evaluation of models of varying sizes to multi-agent AI systems and AI models deployed on physical systems).
Position description
Category
Miscellaneous
Contract
Internship
Job title
Internship Reinforcement learning of VLMs for table understanding-Saclay-H/F
Subject
Based in Saclay (Essonne), the LIST is one of the two institutes of CEA Tech, the Technological Research Division of the CEA. Dedicated to intelligent digital systems, its mission is to carry out technological developments of excellence on behalf of industrial partners, in order to create value.
Within the LIST, the Laboratory of Textual and Visual Semantic Analysis (LASTI) conducts its research in the field of natural language processing and computer vision to extract, classify and generate information. The laboratory's research themes include learning with few data, trustworthiness and multimodality.
Contract duration (months)
6 monhs
Job description
As an intern at the CEA, you will have the opportunity to work within a world-renowned research environment. Our teams consist of passionate and dedicated experts, providing an ideal setting for learning and collaboration. You will have access to state-of-the-art equipment and top-tier research resources to carry out your assignments. The work conducted may potentially lead to a scientific publication.
Context :
The team trains vision-language models (VLMs) that read an image of a table and output its structure. Manual table annotation is expensive, which limits classical supervised approaches.
This internship focuses on training VLMs with reinforcement learning (GRPO), using reward signals that do not depend on human annotations: for example, checking the geometric consistencies or generating synthetic tables whose structure is known by construction. The central question is which annotation-free signals correlate well with the real quality of a prediction, and how to combine them to improve the model on real documents.
What do we expect from you?
Get started with the team's training and evaluation environment
Analyse automatic evaluation methods
Propose and implement new approaches, and validate them through experiments
Work on the performance of the pipeline and the robustness of the models
Evaluate the models on public benchmarks
Document the results
The intern works on an existing pipeline, with access to a GPU cluster (Python, PyTorch, HuggingFace ecosystem, distributed training, experiment tracking). Supervision research engineers of the team, with a weekly meeting.
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Methods / Means
python linux
Applicant Profile
Students in their final year of studies (M2 or engineering school)
Python and PyTorch, Linux
Knowledge of deep learning and statistics
Good level of English
Appreciated: experience with HuggingFace Transformers, notions of reinforcement learning (GRPO, DPO, …)
Position location
Site
Saclay
Job location
France, Ile-de-France, Essonne (91)
Location
Saclay
Candidate criteria
Languages
English (Intermediate)
Prepared diploma
Bac+5 - Diplôme École d'ingénieurs
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