MLOps Engineer (Machine Learning, MLFlow, Kubernetes, DVC)

Choosing Capgemini means choosing a company where you will be empowered to shape your career in the way you’d like, where you’ll be supported and inspired by a collaborative community of colleagues around the world, and where you’ll be able to reimagine what’s possible. Join us and help the world’s leading organizations unlock the value of technology and build a more sustainable, more inclusive world. Your Role As an MLOps Engineer, you will ensure that machine learning models are efficiently deployed, monitored and maintained across environments.

Your responsibilities will include automating model deployment and updates, implementing CI/CD pipelines for ML workflows, optimizing ML models, and setting up monitoring and logging to support reliable production operations. You will also contribute to GenAI-ready delivery by supporting model lifecycle practices for LLM-based, RAG-based or agentic solutions where such patterns are relevant to client needs. Working with diverse and technically advanced solutions will allow you to build strong relationships with clients and continuously grow your expertise.

You will be part of highly self-organizing, independent teams that operate in agile and lean engineering environments, fostering continuous improvement and innovation. Your project Cloud & Custom Applications (C&CA) provides comprehensive end-to-end IT services from business specification, through software development and implementation, to application maintenance using leading IT