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Data Engineer IA (Rag..) - English & French - Based in Lyon full-time - Freelance

Entreprise
Localisation
Lyon, France
Sur site
Type de contrat
Freelance
Niveau

Salaire du marché

Médiane du marché
440€/j
Estimation
390€/jfourchette habituelle465€/j

Cette offre n'affiche pas de salaire. D'après 11 offres pour ce poste (tous niveaux, Lyon), le marché se situe autour de 440€/j (390€/j–465€/j).

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Description du poste

One requirement is to be based in Lyon or closed to Lyon. Please apply if you are concerned

Mission Description

In collaboration with the Data & AI team, you will be involved across the entire

lifecycle of AI solutions:

1. AI Solution Design and Development

- Estimate, design, and implement AI solutions, from POC phase to

industrialization.

- Leverage AI models via:

o generative model APIs (LLMs),

o Python AI libraries and frameworks (Scikit-learn, SpaCy,

LangChain, LangGraph…).

° Design and optimize prompts and AI pipelines.

- Implement RAG architectures.

- Connect AI solutions to data and the Groupe ecosystem (SQL,

tool calling, MCP).

- Write associated technical and functional documentation (interface

contracts, user guides, etc.).

2. Industrialization and Deployment (CI/CD & Cloud)

- Deploy AI APIs and workflows on AWS cloud (ECS, Lambda, etc.).

- Containerize solutions using Docker.

- Create simple testing and demo interfaces (Streamlit).

- Integrate solutions into CI/CD pipelines:

o automation of tests, builds, and deployments,

o use of tools such as Jenkins, GitHub Actions, Terraform.

- Manage access and ensure security, compliance, and data protection.

3. Operations, Performance, and Optimization

- Ensure operational stability of solutions: high availability, performance,

etc.

- Implement MLOps / monitoring practices and respond quickly to

incidents.

- Analyze technical performance and costs of deployed solutions.

- Provide recommendations to optimize architecture and cloud costs.

4. Collaborative Work & Knowledge Sharing

- Contribute to collective engineering practices:

o version control and code reviews via GitHub,

o design and sharing of common components, packages, or

frameworks.

- Support upskilling of internal teams: training and best practices.

- Maintain continuous technology watch on AI and GenAI

advancements.

Exigences du poste

Stack technique :

LLMArtificial Intelligence

Plan d'action

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À propos de l'entreprise

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