Consultant(e) Senior - Ingénieur MLOps / Architecte Solution - AI4B - IDF
Core
End-to-end lifecycle management of AI models from experimentation to large-scale industrialization, including LLM solution implementation and MLOps/LLMOps pipeline maintenance.
Role type
Senior Machine Learning Engineer / MLOps Architect
Builds
Production-ready AI models, LLM services (RAG, fine-tuning), and scalable MLOps/LLMOps infrastructure
Domain
Artificial Intelligence, Machine Learning, Generative AI, Cloud Infrastructure
Deliverable
production ML models | infrastructure
Required skills
Python (pandas, numpy), Machine Learning concepts, Generative AI & LLMs (RAG, embeddings, prompting, fine-tuning), DevOps (CI/CD, Docker, Kubernetes, IaC), MLOps tools (MLflow, Airflow, Kubeflow), Cloud platforms (AWS, Azure, GCP, OVH, Scaleway)
Preferred skills
Experience with GPU/TPU resource management, professional spoken/written English
Technologies
MLflow, Airflow, Kubeflow, Langgraph, HuggingFace, PyTorch, TensorFlow, scikit-learn, Docker, Kubernetes, AWS, Azure, GCP, OVH, Scaleway
Responsibilities
Collaborate with Data Scientists to design, train, evaluate, and improve ML models; Optimize PoC results for field problems; Implement LLM-based solutions; Version experiments and models; Prepare prototypes for production; Deploy AI models and services; Implement production monitoring (drift, performance, logs, LLM quality); Manage cloud/on-prem infrastructure and compute resources; Provide tooling recommendations for MLOps/LLMOps chains
Seniority
Mid-Senior (2-3 years experience)