Machine Learning Engineer / Déploiement IA & MLOps F/H
Core
End-to-end lifecycle management of AI models including development, training, optimization, deployment, and monitoring for NLP, vision, and prediction use cases.
Role type
Senior Machine Learning Engineer (MLOps)
Builds
Production ML models, automated ML pipelines, and cloud-based AI services
Domain
Artificial Intelligence / Machine Learning / Cloud Infrastructure
Deliverable
production ML models
Required skills
Machine Learning, Deep Learning, Python (production), MLOps, CI/CD, Docker, Cloud platforms (AWS/GCP/Azure), API development, Model monitoring and evaluation
Preferred skills
Java, Scala, Spark, FastAPI, GitLab
Technologies
PyTorch, TensorFlow, Scikit-learn, Docker, FastAPI, AWS SageMaker, Google Vertex AI, Git, GitLab
Responsibilities
Develop, train, and optimize ML/DL models; Design and maintain ML production pipelines; Package, version, and deploy models via APIs or containers; Implement monitoring and observability solutions; Collaborate on cloud architecture; Advise clients on AI scalability and industrialization; Define internal AI engineering standards
Seniority
Senior, hands-on IC