AI role · Open offer

Senior MLOps Engineer

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Focus: AI Platform

Paris · 200-500 employees · Scale-up · GenAI: Yes

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: Full-time
Workplace: Hybrid
Location: 33 Rue La Fayette, Paris, IDF 75009, France
Compensation: EUR 78k-98k/year + bonus
Experience level: Senior
Team: AI Platform
Benefits & perks

About this role

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

Hugging Face is hiring a Senior Senior MLOps Engineer on the AI Platform team (Hybrid · 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.

Hugging Face — Open-source hub for models and datasets

Role context: AI Platform · based in Paris · ~200-500 people · Scale-up · LLM/genAI focus: Yes.

You will own delivery across the AI lifecycle—data and evaluation, modeling or LLM-based features, production rollout, and close collaboration with product and domain experts—with pragmatic ownership and clear stakeholder communication.

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.
Kubernetes
Deploying and scaling model services with health checks, autoscaling, and rollout discipline.
AWS

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.

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: Apply from this listing on Ganloss so your candidate profile, optional CV link, and cover note reach the hiring team together.
Several of these show up in recent shipped work—not only on your CV: Python, Kubernetes, AWS, 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 are comfortable with the hybrid rhythm (Hybrid · Paris, 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

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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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