AI Engineer & MLOps Specialist
Versatile Python developer with expertise in Machine Learning, Generative AI, Agentic Systems, and production‑grade MLOps pipelines. Cloud‑native. Automation‑first.
With over a decade in airport IT systems management and certified AI specialization, I bridge the gap between rigorous engineering and cutting‑edge artificial intelligence. Based in Laval, Québec, I design and ship end‑to‑end AI solutions — from raw data ingestion to production‑grade model deployment.
My background includes managing large‑scale DCS/Amadeus system migrations for Air Algérie and training hundreds of flight operations agents — giving me a unique perspective on building AI products that actually work in high‑stakes environments.
End-to-end predictive systems with full MLOps pipelines, deployed across multi-cloud environments.
Predicted key KPIs (passenger, freight, and mail volumes) using real BTS (US) datasets. Full MLOps automation with end-to-end CI/CD, achieving over 93% predictive accuracy.
Production-grade attrition prediction system deployed across GCP, Azure, AWS, and Hugging Face. Integrated full MLOps stack with drift detection via Evidently AI, improving retention accuracy by 20%.
Complete end-to-end MLOps pipeline with DVC for data versioning, MLflow for experiment tracking, and GitHub Actions for automated CI/CD workflow management.
Neural network architectures tackling complex real-world prediction and analysis challenges.
Recurrent neural network system leveraging LSTM architecture for multi-step time series forecasting of aviation and logistics demand — integrated with Streamlit dashboards for real-time visualization.
Deep learning NLP pipeline for automated document classification and information extraction using transformer‑based embeddings with vector database storage for semantic search and retrieval.
Autoencoder‑based deep learning system for real-time anomaly detection in operational data streams, trained on flight operations metrics with live alerting and Power BI integration.
Practical GenAI applications that integrate LLMs with real data and production-ready interfaces.
Multi-agent CV analysis and enhancement system built with CrewAI, DeepSeek API, OpenAI, and Streamlit. Reduced relevant profile selection time by 70%.
Retrieval-Augmented Generation system enabling employees to query internal knowledge bases with natural language. Built with LangChain, ChromaDB, and Pinecone for scalable semantic retrieval.
Production-ready chatbot suite built with LangFlow for visual pipeline design, integrating text, document, and structured data understanding with Google Studio AI and Groq backends.
Autonomous multi-agent systems that plan, reason, and execute complex workflows end-to-end.
End-to-end AI agent for travel planning with CrewAI, Gemini API, and Streamlit. Automated over 90% of the user planning process with REST API and full CI/CD integration.
Deployed 6+ autonomous multi-agent systems using LangGraph, Google Studio AI, and Groq. Agents capable of tool use, web browsing, document processing, and cross-agent delegation.
Agentic workflow automation combining CrewAI and LangGraph to orchestrate complex multi-step business processes — from data extraction and transformation to report generation and decision support.
Open to AI Engineer, MLOps, and Data Science roles. Let's build something remarkable.