Research Engineer in Artificial Intelligence for Experimentation on the Combination of AI and Formal Methods

Inria Rennes; Rennes; On-site; EUR 42,000 - 58,000; Full time

Job summary

Inria Rennes is seeking a candidate to join the FRAIME project, working across five Inria teams and two MERCE teams. You will monitor, deploy, evaluate, and share AI technologies, while coaching researchers with hands-on experience in AI tools.

You will interact with researchers in formal methods, software engineering, and AI, and you will use computing facilities like Ilaas and Albert to run experiments. This is a collaborative, research-driven role at the Rennes center.

Qualifications

• Master’s degree in Computer Science, AI, or related field.
• Experience with RL/LLM/SLM technologies.
• Ability to design, run, and analyze experiments with reproducibility.
• Strong written and spoken English for collaboration.

Responsibilities

• Identify technologies relevant to the experiments.
• Monitor technologies related to the project (LLMs, SLMs).
• Deploy infrastructure that can be used throughout the project.
• Implement evaluation methods for the experiments.
• Provide researchers involved in the project with hands-on experience in AI technologies; proactively recommending technologies to be used.
• Contribute to the sharing of know-how on AI technologies within the project.
• Produce summaries of the experiments and present at plenary meetings.

Skills

RL/LLM/SLM

Fine-tuning

RAG

Prompt engineering

Quantization

Inference optimization

CI/CD

Git

Software project mgmt

Education

Master’s degree in CS/AI

Tools

Git

CI/CD pipelines

Job description

Context

The widespread adoption of AI across many areas of society calls for the development of techniques to make AI safer and more trustworthy. AI-based systems deliver impressive performance, but their lack of transparency makes them difficult to trust in industrial applications, as they provide no formal guarantees. Conversely, formal methods excel at logical reasoning and can prove properties of programs or detect errors, but they often face scalability limitations.

To address this challenge, Inria and MERCE (Mitsubishi Electric R&D Centre Europe) have launched a joint project, called Défi FRAIME, to explore, on the one hand, how formal methods can provide guarantees for AI systems and, on the other hand, how AI can help make formal methods more efficient and easier for practitioners to use. The vision of the project is to intertwine formal methods and AI to efficiently design safe systems. The project is driven by industrial use cases in MERCE’s areas of expertise.

Assignment

This position is part of the FRAIME project, which provides a stimulating collaborative research environment involving 5 Inria teams and 2 MERCE teams, and will offer the successful candidate the opportunity to interact with around twenty recognized researchers in formal methods, software engineering, and AI. The position aims to ensure the monitoring, deployment, evaluation, and sharing of AI technologies within the project, while providing researchers with hands‑on expertise and consolidating the knowledge gained through experimentation. The successful candidate will have access to following computing facilities: Ilaas: https://www.ilaas.fr/ Albert: https://ia.numerique.gouv.fr/outils-ia/albert-api/ Abaca: (Inria internal computing infrastructure). The successful candidate will be based at the Inria Centre at the University of Rennes and will interact frequently with the MERCE teams (located nearby) and with the Inria teams in Nantes and Paris involved in Défi FRAIME.

Main activities

• Identification of technologies relevant to the experiments.
• Monitoring of technologies related to the project (LLMs, SLMs).
• Deployment of infrastructure that can be used throughout the project.
• Implementation of evaluation methods for the experiments.
• Providing researchers involved in the project with hands-on experience in AI technologies; proactively recommending technologies to be used.
• Contributing to the sharing of know-how and knowledge on AI technologies within the project.
• Consolidation and sharing of knowledge acquired within the project.
• Production of summaries of the experiments conducted, and presentation at plenary meetings.

Skills

Required Technical Skills

• Proficiency in RL / LLM / SLM technologies: fine-tuning (PEFT/LoRA), RAG, prompt engineering, quantization, inference optimization, technical infrastructure (local and remote deployment).
• Ability to conduct experiments (benchmark design, reproducibility, and experiment tracking), analyze results, and evaluate AI systems.
• Proficiency with collaborative development tools and practices (Git, continuous integration, software project management).
• Master’s degree or equivalent in Computer Science, Artificial Intelligence, Applied Mathematics, or a related field.

Additional Assets / Desirable Extra Skills

• Experience with formal methods would be a plus.
• Knowledge of energy measurement technologies would be an asset.
• Knowledge of agentic frameworks would be a plus.

Soft Skills

• Professional proficiency in written and spoken English.
• Strong written and oral communication skills.
• Ability to work effectively as part of a team in a collaborative research environment.
• Ability to work independently in project execution and problem solving.
• Coordination skills.
• Ability to interact with people from a variety of disciplines (AI, formal methods, software engineering).