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MLOps Engineer — enterprise AI platform
Dataiku
Cette annonce est pensée pour les profils IA : compétences et outils clairs pour savoir si le poste correspond avant de postuler — et pour réduire les mauvais matchs au screening.
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Type d’emploi
Lieu de travail Hybrid
Localisation 203 Rue de Bercy, Paris, IDF 75012, France · Hybrid
Rémunération EUR 75k-98k/year + bonus Niveau d’expérience Avantages Mutuelle, télétravail partiel, formation. Comment postuler Déploiement modèle avec monitoring drift en contexte client.
Publiée le 21 juin 2026
Mise à jour 8 juil. 2026 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). 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.
✓ 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. Ce que l’employeur demande
Déploiement modèle avec monitoring drift en contexte client.
Connectez-vous avec un compte candidat pour postuler
Inscrivez-vous, ajoutez une accroche et une bio, puis vous pourrez joindre un lien ou un PDF de CV dans Mon compte avant de postuler. Vos candidatures restent liées à votre profil et les employeurs voient plus facilement votre parcours.
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Intitulé
MLOps Engineer — enterprise AI platform
Postuler Pensé pour les équipes qui recrutent des personnes qui travaillent avec l’IA, pas seulement autour.
Les candidats voient compétences et outils dès le départ ; vous recevez des candidatures structurées dans un seul tableau de bord.
Touchez les praticiens IA qui parcourent les offres avec des attentes « preuve d’abord ».
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