> Markdown version of [/jobs/ext/1244823-ml-engineer](https://www.wearedevelopers.com/jobs/ext/1244823-ml-engineer). Every page supports `.md` or `Accept: text/markdown`. Links point to the HTML versions so they work for humans too. Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # ML Engineer - **Company:** Tilencia - **Location:** Paris, France - **Experience:** Experienced - **Contract:** Permanent contract - **Skills:** Continuous Integration, Machine Learning, Data Processing, Chatbots, Generative AI, Machine Learning Operations - **Published:** July 12, 2026 - **Apply:** https://fr.indeed.com/viewjob?jk=fd79bdd608793816 ## About the Role 3 ans d'expérience Solide expérience en Machine Learning / NLP. ## Description * L'humain au centre * Détection de talents * Suivi, coaching * Solutions cousues main Et surtout prendre du plaisir ;, Nous recherchons un Machine Learning Engineer spécialisé en NLP / IA Générative pour concevoir, entraîner et déployer des voicebots et chatbots de nouvelle génération, de bout en bout (du besoin métier à la mise en production). Cadrage & conception Recueillir et formaliser les besoins métiers (parcours vocaux, scénarios de conversation, KPIs) Concevoir les architectures conversationnelles (voicebot, chatbot). Modélisation & entraînement Entraîner, adapter et évaluer des modèles NLP Travailler avec les briques voix (ASR / TTS) et les intégrer dans la chaîne conversationnelle. Industrialisation & déploiement Mettre en place les pipelines MLOps (préparation des données, entraînement, évaluation, CI/CD) Assurer le suivi en run : monitoring qualité, dérive, optimisation continue Amélioration continue Analyser les logs de conversations, identifier les axes d'amélioration Proposer et implémenter des améliorations de modèles, de prompts, de flux conversationnels Collaborer étroitement avec les équipes métiers, IT et relation client ## Related Videos - [How E.On productionizes its AI model & Implementation of Secure Generative AI.](https://www.wearedevelopers.com/videos/623-how-e-on-productionizes-its-ai-model-implementation-of-secure-generative-ai) - [Chatbots are going to destroy infrastructures and your cloud bills](https://www.wearedevelopers.com/videos/1130-chatbots-are-going-to-destroy-infrastructures-and-your-cloud-bills) - [Your imaginations is (no longer) the limit: how Generative AI empowers people to be creative](https://www.wearedevelopers.com/videos/741-your-imaginations-is-no-longer-the-limit-how-generative-ai-empowers-people-to-be-creative) - [Implementing continuous delivery in a data processing pipeline](https://www.wearedevelopers.com/videos/73-implementing-continuous-delivery-in-a-data-processing-pipeline) - [Introduction to Azure Machine Learning](https://www.wearedevelopers.com/videos/368-introduction-to-azure-machine-learning) - [Testing AI Agents: Automated Evaluation for Chatbots & RAG Systems](https://www.wearedevelopers.com/videos/100300-testing-ai-agents-automated-evaluation-for-chatbots-rag-systems) ## Related Articles - [How to Become an AI Engineer](https://www.wearedevelopers.com/magazine/331-how-to-become-an-ai-engineer) - [What Are Large Language Models?](https://www.wearedevelopers.com/magazine/304-what-are-large-language-models) - [Coffee with Developers - Maria Apazoglou - Making AI understandable for all in production](https://www.wearedevelopers.com/magazine/475-coffee-with-developers-maria-apazoglou-making-ai-understandable-for-all-in-production) - [MLOps – What’s the deal behind it?](https://www.wearedevelopers.com/magazine/125-mlops-what-s-the-deal-behind-it) - [MLops – Deploying, Maintaining And Evolving Machine Learning Models in Production](https://www.wearedevelopers.com/magazine/115-mlops-deploying-maintaining-and-evolving-machine-learning-models-in-production) - [MLOps And AI Driven Development](https://www.wearedevelopers.com/magazine/82-mlops-and-ai-driven-development)