AI role · Open offer
Senior ML Engineer — cloud observability
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
- 255 Rue Francis de Pressensé, 34170 Castelnau-le-Lez, France · Hybrid
- Compensation
- EUR 55k–75k/year + BSPCE
- Experience level
- Senior
- Team
- Platform AI
- Benefits & perks
About this role
What the team is looking for and how this position fits.
OVHcloud is hiring a Senior Senior ML Engineer — cloud observability on the Platform AI team (Hybrid · Castelnau-le-Lez, 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** is Europe's leading **hyperscaler** — bare metal, public cloud, and observability from engineering sites including **Castelnau-le-Lez** near Montpellier.
Senior ML Engineer (hybrid): **anomaly detection**, **capacity forecasting**, and **SRE copilots** on petabyte-scale telemetry.
About OVHcloud
- French cloud champion with global datacenter footprint.
- Montpellier metro team focuses on platform reliability AI.
- Strong open-source and EU data-sovereignty culture.
What you will do
- Detect incidents early from metrics, logs, and traces.
- Forecast power and bandwidth for datacenter planning.
- Build RAG assistants for runbook navigation.
Stack & environment
- Python, PyTorch, Spark, Prometheus, Kubernetes.
- Hybrid Castelnau-le-Lez; French and English teams.
What we look for
- 4+ years ML for observability or infra.
- Eligible to work in France.
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.
- PyTorch
Training and inference with PyTorch: reproducible experiments, checkpointing, and deployment-minded exports.
- SQL
Tools & stack
Platforms and products mentioned for this role (APIs, IDEs, vector DBs, CRMs, design tools, etc.).
- KubernetesTool
Deploying and scaling model services with health checks, autoscaling, and rollout discipline.
- 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: Anomaly detection or capacity forecasting on hyperscale infra logs.
- ✓Several of these show up in recent shipped work—not only on your CV: Python, PyTorch, SQL, Spark, and Kubernetes.
- ✓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 · Castelnau-le-Lez, 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
Anomaly detection or capacity forecasting on hyperscale infra logs.
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