Omar LALMICHE

Building an ENT clinical conversational assistant from the ground up at Institut Pasteur, with a focus on LLMs, retrieval-augmented generation (RAG), evaluation, deployment, and healthcare AI integration. My work spans literature review, architecture design, benchmarking, implementation, and MLOps-oriented thinking to build reliable, scalable, and clinically relevant conversational AI systems. I also explore safety, groundedness, traceability, and integration constraints with healthcare environments such as CoreMed, with the goal of delivering a production-ready clinical AI product.

As a final-year intern, I contributed to a collaborative project between Youcode and OCP Group’s Social & Cultural Service in Youssoufia, developing the full-stack web application ("OCP Activity Booking App") to digitize and manage registrations for social activities. I worked closely with cross-organizational teams to define user requirements and ensure alignment with departmental objectives. Leading the project end-to-end, I built an intuitive front-end using React, and developed a robust back-end leveraging Node.js and Python (Flask) to manage registration workflows efficiently. Additionally, I created an interactive dashboard for real-time data visualization and analytics, enhancing decision-making. The solution included an AI-powered chatbot for user assistance and utilized MySQL (JawsDB) for secure data management. This significantly streamlined processes, improving efficiency, transparency, and user satisfaction by transitioning from manual methods to a modern digital platform.

Completed a two-month internship at OCP Group’s Youssoufia Phosphate Drying Plant, focused on applying data science techniques to industrial maintenance. • Built a data pipeline: data collection, cleaning and preprocessing with Python (Pandas, NumPy). • Performed exploratory data analysis (EDA) and applied machine learning models (Random Forest, Logistic Regression) to predict equipment failures. • Created data visualizations with Matplotlib and Seaborn to support decision-making. • Collaborated with the technical team to enhance data reliability and optimize maintenance strategies. This internship strengthened my skills in data analysis, machine learning, and data-driven problem solving, while providing practical exposure to the industrial sector.