{"id":4014699,"url":"https://alion.io/job/groupe-celad-devops-data-mlops-fh","title":"DevOps Data / MLOps (F/H)","company":{"id":3908314,"name":"Groupe CELAD","domain":"celad.com","url":"https://alion.io/company/celad-2","size_band":null,"is_staffing_agency":false,"employer_type":"services","is_intermediary":false,"listed_via":null,"ats_vendor":null,"truth_index":null},"role":"DevOps","role_family":"DevOps","seniority":null,"employment_type":"freelance","work_mode":"hybrid","remote_scope":null,"remote_scope_basis":null,"remote_working_hours":null,"hiring_geo_confidence":"structured","locations":["Lyon, France"],"countries":["FR"],"hiring_countries":[],"hiring_countries_total":0,"salary":{"min":400,"max":470,"currency":"EUR","period":"day","gross":null,"usd_annual":131750},"salary_estimate":null,"experience_years_min":null,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"CI/CD","optional":false},{"name":"Kubernetes","optional":false},{"name":"Machine Learning","optional":false},{"name":"PostgreSQL","optional":false},{"name":"pySpark","optional":false},{"name":"Python","optional":false},{"name":"Spark","optional":true}],"status":"live","first_seen_at":"2026-11-10T09:46:57Z","employer_posted_date":null,"last_verified_at":"2026-11-10T09:46:57Z","board_verified":false,"closed_at":null,"days_open":0,"trust":{"level":"not_scored","repost_count":null,"flags":[],"days_open":0},"description":"A LIRE ATTENTIVEMENT AVANT DE POSTULER ⬇\n🏠 2 jours de télétravail / semaine - 📍 Lyon (07) - 🛠 Expérience de 5 ans minimum\n\nEnvie de rejoindre une équipe où la tech et les projets stimulants sont au rendez-vous ? Cette opportunité est faite pour vous ! 🚀\n\nNous poursuivons notre développement et recherchons actuellement un.e DevOps Data / MLOps pour intervenir chez un de nos clients. 💻💼\n\nContexte : Dans le cadre du développement et de l'exploitation de plusieurs produits Data stratégiques, nous recherchons un DevOps Data / MLOps afin d'accompagner des équipes Data Science et Data Engineering sur l'ensemble du cycle de vie de leurs solutions.\nLes produits concernés s'appuient principalement sur des pipelines de traitement de données massives, des modèles de Machine Learning en production, ainsi que des applications web et API à forte valeur métier.\nLe/la consultant.e interviendra à la fois sur les sujets de Build, Run, automatisation, observabilité et industrialisation des plateformes Data.\n\nVoici un aperçu détaillé de vos missions : 🎯\nIndustrialisation et CI/CD\n- Concevoir et maintenir les chaînes CI/CD des applications et traitements Data\n- Industrialiser les déploiements des pipelines Python et PySpark\n- Automatiser les processus de livraison des applications web, API et composants Data\n\nExploitation et Run\n- Assurer le maintien en conditions opérationnelles des produits\n- Superviser les traitements en production\n- Garantir la disponibilité et la performance des environnements\n- Participer au support technique de premier niveau\n\nObservabilité et Monitoring\n- Mettre en place et faire évoluer les dispositifs d'observabilité\n- Concevoir les métriques techniques et tableaux de bord de supervision\n- Analyser les incidents et conduire les actions d'amélioration continue\n\nInfrastructure et Automatisation\n- Développer et maintenir l'infrastructure-as-code\n- Administrer les environnements de développement, préproduction, production et laboratoires Data\n- Piloter les évolutions techniques liées à la sécurité, aux vulnérabilités et aux mises à niveau des composants\n\nAccompagnement des équipes Data\n- Collaborer étroitement avec les Data Scientists et Data Engineers\n- Faciliter la mise en production des modèles de Machine Learning\n- Assurer l'interface avec les équipes infrastructures, sécurité et plateformes techniques\nProfil recherché\nLes compétences que nous recherchons : 🔎\nVous disposez d’une solide expertise sur :\n- Les environnements DevOps et Cloud Native.\n- Kubernetes et la conteneurisation.\n- L'infrastructure-as-code.\n- Les réseaux et systèmes.\n- La sécurisation des flux (TLS notamment).\n- L'administration de machines virtuelles.\n- Le monitoring et les métriques applicatives.\n- Python et les environnements Data.\n\nVous êtes également à l'aise avec :\n- Les traitements Big Data sous PySpark.\n- Les pipelines Data à fort volume.\n- L'administration PostgreSQL.\n- Les environnements de Data Science et de Machine Learning en production.\n- Les architectures multi-environnements (Lab, Dev, Préprod, Prod).\n\nSi vous êtes prêt.e à relever ce défi et à contribuer à des projets stimulants, n'hésitez pas à postuler dès maintenant ! 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