AI role · Open offer

GenAI Engineer — cloud platform

OVHcloud

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.

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At a glance

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

Employment: Permanent (CDI), Full-time
Workplace: Hybrid
Location: 2 Rue Kellermann, Roubaix, HDF 59100, France · Hybrid
Compensation: EUR 55k–75k/year + intéressement
Experience level: Senior
Team: AI products
Benefits & perks

About this role

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

OVHcloud is hiring a Senior GenAI Engineer — cloud platform on the AI products team (Hybrid · Roubaix, 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.

OVHcloud (Roubaix) : cloud souverain et services GenAI EU.

GenAI Engineer : API LLM, fine-tuning, observabilité inference.

Missions

Offering LLM managée sur infra OVH.
Benchmarks coût/latence.

Stack & environnement

Python, Kubernetes, LangChain, GPU.

Profil recherché

MLOps ou platform engineering.

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.
Kubernetes

Tools & stack

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

PyTorchTool
Training and inference with PyTorch: reproducible experiments, checkpointing, and deployment-minded exports.
DockerTool
Containerized services and reproducible dev environments for ML and LLM workloads.

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: API LLM managée, fine-tuning client ou observabilité inference.
Several of these show up in recent shipped work—not only on your CV: Python, LangChain, Kubernetes, MLOps, and PyTorch.
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 are comfortable with the hybrid rhythm (Hybrid · Roubaix, France)—onsite collaboration when it matters, deep work when remote.
You explain trade-offs (quality, cost, latency, safety) in plain language—with numbers or examples, not buzzwords.

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What the employer asked for

API LLM managée, fine-tuning client ou observabilité inference.

Register, add a headline and bio, then you can attach a CV link or PDF on My account before you apply. That keeps applications tied to your profile and makes it easier for employers to review your background.

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