Mohamed Kabbaj

Data Scientist & MLOps Engineer | Télécom Paris Master's Degree | 5 years of experience

Looking for an expert capable of designing, deploying, and maintaining reliable AI systems in production? I can help you.

With a background in statistics engineering (INSEA, class valedictorian) and currently specializing in AI & MLOps at Télécom Paris, I assist my clients from the experimentation phase to the production of scalable, reproducible, and monitored ML solutions.

What I bring to you:

Design and deployment of Machine Learning models in production (credit scoring, fraud detection, recommendation systems)

State-of-the-art LLM architectures: fine-tuning (LoRA), RAG, Graph RAG, and multi-agent systems (Agentic AI)

Model Explainability (XAI) to meet European AI Act requirements (SHAP, Integrated Gradients)

End-to-end MLOps pipelines: CI/CD, drift monitoring, model versioning (MLflow, DVC, Docker, Kubernetes)

Data Engineering & Big Data: ETL pipelines, distributed architectures (Spark, HDFS), decision-making dashboards

My references:

ML Engineer at CIH Bank: Industrialized credit scoring and fraud detection in production

Covéa project (Télécom Paris): Legal explainability engine based on autonomous agents and LLMs for insurance

Data Engineer at the Ministry of Higher Education (3 years): National decision-making architecture and statistical modeling

Freelance Data Scientist Consultant: Agro-climatic modeling and satellite image analysis

Big Data Infrastructure: 5-node cluster, distributed processing of 16 GB / 71M rows

Technical Stack: Python, PyTorch, Transformers, LangChain, LangGraph, Scikit-learn, XGBoost, Docker, Kubernetes, MLflow, Airflow, Spark, SQL, Neo4j, FastAPI

Available for Data Science, MLOps, GenAI, and Data Engineering assignments. Contact me to discuss.