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AI role · Open offer

MLOps Engineer — enterprise AI platform

Dataiku

Permanent (CDI)
Full-time
Senior
MLOps
Hybrid
203 Rue de Bercy, Paris, IDF 75012, France · Hybrid
Paris, France
EUR 75k-98k/year + bonus

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: 203 Rue de Bercy, Paris, IDF 75012, France · Hybrid
Compensation: EUR 75k-98k/year + bonus
Experience level: Senior
Team: MLOps
Benefits & perks: Mutuelle, télétravail partiel, formation.
How to apply: Déploiement modèle avec monitoring drift en contexte client.
Company site: www.dataiku.com
Listed: Jun 21, 2026
Updated: Aug 3, 2026

About this role

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

Dataiku is hiring a Senior MLOps Engineer — enterprise AI platform on the MLOps 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.

Dataiku est une plateforme enterprise AI end-to-end utilisée par les grandes organisations. MLOps et gouvernance sont au cœur du produit.

Ingénieur·e MLOps (Paris) : déploiement modèles, monitoring drift, et intégration LLM dans les projets clients.

What you will do

Ship production MLOps enterprise with clear evaluation, monitoring, and rollback paths—not demo-only notebooks.
Partner with product, design, and domain experts on requirements, trade-offs, and safe rollout.
Improve data quality, labeling, and offline metrics that correlate with business KPIs.
Document architectures and runbooks for on-call and customer-facing teams.
Mentor engineers on testing, observability, and responsible AI practices.

What we look for

Strong Python and modern ML/LLM stack experience with multiple shipped features.
Comfort with SQL, experimentation, and communicating results to non-technical stakeholders.
Pragmatic ownership from prototype to production—including cost and latency budgets.
Eligible to work in the listed country; professional English (French a plus for Paris roles).

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.
Docker
Containerized services and reproducible dev environments for ML and LLM workloads.

Tools & stack

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

AWSTool
Regular use of AWS 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: Déploiement modèle avec monitoring drift en contexte client.
Several of these show up in recent shipped work—not only on your CV: Python, Kubernetes, Docker, and AWS.
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.
You read the full listing (comp: EUR 75k-98k/year + bonus, benefits in At a glance) and your expectations align.

Apply

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What the employer asked for

Déploiement modèle avec monitoring drift en contexte client.

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