AI role · Open offer

Ingénieur LLM freelance — mission RAG

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Mistral AI

Freelance
Senior
Professional services
Remote
15 Rue des Halles, Paris, IDF 75001, France · Remote
Paris, France
EUR 700–950/day

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At a glance

How you'll work, where, and key listing dates.

Employment: Freelance
Workplace: Remote
Location: 15 Rue des Halles, Paris, IDF 75001, France · Remote
Compensation: EUR 700–950/day
Experience level: Senior
Team: Professional services
Benefits & perks

About this role

What the team is looking for and how this position fits.

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.

Skills we're hiring for

What each capability means for this role—not a keyword checklist.

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

Tools & stack

Platforms and products mentioned for this role (APIs, IDEs, vector DBs, CRMs, design tools, etc.).

DockerTool
Containerized services and reproducible dev environments for ML and LLM workloads.
vLLMTool
Regular use of vLLM in the LLM & generative AI stack—configuration, debugging, and team conventions.

You're a strong fit if…

Tailored to this listing—use it as a self-check before you apply.

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.

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What the employer asked for

Mission RAG enterprise livrée avec evals et handover documenté.

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