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AI role · Open offer
Ingénieur LLM freelance — mission RAG
Mistral AI
This listing is optimized for AI-native talent : clear skills and tools so candidates know if they fit before they apply—and so you spend less time screening mismatches.
4 skills 2 tools
Workplace Remote
Location 15 Rue des Halles, Paris, IDF 75001, France · Remote
Compensation EUR 700–950/day Team Professional servicesBenefits & perks Mission 4 mois renouvelable, remote France. How to apply Mission RAG enterprise livrée avec evals et handover documenté.
Listed Jan 7, 2027 Mistral AI is hiring a Senior Ingénieur LLM freelance — mission RAG on the Professional services team (Remote · Paris, France). This is a hands-on role in LLM & generative AI —not a generic “AI enthusiast” post.
You will own LLM features, retrieval, agents, and evaluation end to end: problem framing, offline evaluation, safe rollout, and iteration from production signals. Success is measured with clear metrics (quality, latency, cost, or business KPIs)—not slide decks alone.
Mistral AI déploie des LLM multilingues pour l'enterprise — missions conseil RAG et fine-tuning pour clients européens.
Ingénieur LLM freelance (remote France, syncs Paris) : mission 4 mois renouvelable — industrialisation RAG, evals et handover équipe client.
À propos de la mission
Client enterprise européen (secteur régulé). Livrables : pipeline RAG, métriques qualité, documentation runbook. Collaboration avec research Mistral sur modèles propriétaires. Missions
Auditer corpus et concevoir architecture retrieval + génération. Fine-tuner et benchmarker modèles Mistral sur jeux métier. Former équipe interne et transférer ownership. Stack & environnement
Python, LangChain, vLLM, PyTorch, MLflow. Remote France ; 1–2 syncs/semaine Paris possibles. Profil recherché
5+ ans LLM/RAG en consulting ou enterprise. Statut freelance / portage ; TJM selon expérience. Python
Production Python for data pipelines, model code, APIs, and automated tests—not notebook-only workflows.
LangChain
Orchestrating LLM chains, tools, and retrieval with observable steps and failure handling.
OpenAI API
Calling frontier APIs with retries, cost controls, prompt versioning, and safety filters.
PyTorch
Training and inference with PyTorch: reproducible experiments, checkpointing, and deployment-minded exports.
Docker Tool
Containerized services and reproducible dev environments for ML and LLM workloads.
vLLM Tool
Regular use of vLLM in the LLM & generative AI stack—configuration, debugging, and team conventions.
✓ You can show evidence in your application: Mission RAG enterprise livrée avec evals et handover documenté. ✓ Several of these show up in recent shipped work—not only on your CV: Python, LangChain, OpenAI API, PyTorch, and Docker. ✓ You have owned LLM features, retrieval, agents, and evaluation in production: debugging live issues, running postmortems, and iterating from real user or business signals. ✓ You communicate clearly in writing, document decisions, and can overlap with the team’s core hours for pairing and incident response. ✓ You explain trade-offs (quality, cost, latency, safety) in plain language—with numbers or examples, not buzzwords. ✓ You read the full listing (comp: EUR 700–950/day, benefits in At a glance) and your expectations align. What the employer asked for
Mission RAG enterprise livrée avec evals et handover documenté.
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Ingénieur LLM freelance — mission RAG
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