About Me
Transforming Businesses Through AI Innovation
Consultant in Generative AI with 5+ years of experience developing and deploying AI solutions across academia and industry. Specialized in Large Language Models, RAG systems, and enterprise AI solutions with a focus on transforming business operations through intelligent automation.
Proficient in cloud-based machine learning, NLP, and deep learning with extensive experience in TensorFlow, LangChain, and Azure/AWS platforms. Skilled in translating complex business challenges into scalable AI solutions for insurance, technology, and enterprise sectors. Currently pursuing a PhD in Data Science and Machine Learning while delivering strategic consulting services to drive digital transformation and competitive advantage.
Current Role: Leading cutting-edge projects at Exakis Nelite including intelligent document processing with 95% extraction accuracy, enterprise AI chatbots with advanced RAG capabilities, and privacy-first Azure-based conversational AI platforms.
Technical Expertise
AI/ML Frameworks
LLMs & GenAI
AI Specializations
MLOps & Cloud
Data & Tools
Programming
Career Timeline
Generative AI Consultant
Feb 2025 - Present
Exakis Nelite
Casablanca, Morocco
Key Achievements
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Intelligent Document Processing: Architected and deployed end-to-end RPA pipeline combining OCR and LLM technologies for automated invoice and ID processing, achieving 95% extraction accuracy with intelligent validation and seamless database integration
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Enterprise AI Chatbot: Designed and implemented privacy-first Azure-based conversational AI platform featuring advanced RAG capabilities, multi-agent orchestration, and integrated tools including web search and code interpreter
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Agent-Based AI Systems: Built intelligent agent framework with tool-calling capabilities, enabling dynamic web search, code execution, and real-time data retrieval within secure enterprise environments
Technologies Used
Senior Machine Learning Engineer
Jan 2024 - Jan 2025
DXC Technology
Casablanca, Morocco
Key Achievements
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AI Architecture & Implementation: Spearheaded enterprise-scale LLM and generative AI deployment for insurance sector, designing end-to-end AI pipelines that enhanced decision-making processes and customer interactions
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Performance Optimization: Achieved 20% improvement in RAG system accuracy through advanced reranking algorithms and 30% latency reduction via intelligent caching mechanisms for high-frequency queries
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Multimodal AI Development: Engineered and deployed multimodal LLM capabilities enabling simultaneous text and image processing, expanding AI applicability across diverse insurance use cases
Technologies Used
Data Scientist & ML Engineer
Dec 2020 - Dec 2023
BlackStone Eit
Seattle, WA
Key Achievements
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Cloud AI Deployment: Architected and deployed production-grade ML models on AWS and Azure, implementing robust MLOps practices with automated CI/CD pipelines and model versioning
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Multimodal Archive: Developed enterprise archive digitalization system using Azure Video Indexer, enabling intelligent multi-modal search across video/image content with keyword, topic, and visual element recognition
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Geospatial AI: Implemented advanced image segmentation algorithms for satellite imagery analysis, delivering AI-driven insights for urban planning and environmental monitoring applications
Technologies Used
Data Scientist & ML Engineer
June - Dec 2020Key Achievements
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Social Media Mining: Developed comprehensive data scraping infrastructure for social media platforms using Python, Selenium, GraphQL & BeautifulSoup
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Business Intelligence: Generated interactive dashboards and detailed reports using Tableau, Qlik and PowerBI for actionable business insights
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Sentiment Analysis: Implemented advanced Natural Language Processing algorithms to evaluate social media posts & comments using sophisticated sentiment analysis techniques
Technologies Used
Featured Projects
Multimodal LLM for Chart Analysis
Engineered a production-ready AI system combining computer vision and NLP for automated chart analysis, providing detailed textual descriptions and actionable insights from complex visual data.
Customer Churn Prediction AI
Built end-to-end ML pipeline for telecom customer churn prediction using ensemble methods and deep learning, processing 7000+ customer records with real-time inference capabilities.
Intelligent Social Media Extraction
Developed scalable web scraping infrastructure for comprehensive Facebook data extraction, including post analytics, engagement metrics, and multimedia content processing.
Advanced Topic Modeling with BERTopic
Implemented state-of-the-art topic discovery system using BERT embeddings and advanced clustering algorithms for large-scale text analysis and insight extraction.
Time Series Forecasting for Electricity Data
Developed deep learning models (LSTM, GRU) to forecast short-term and long-term electricity consumption patterns with sliding window approach for sequence prediction optimization.
Publications
Integrated Manufacturing-Microgrid Control Using Multi-Agent Deep Reinforcement Learning
IFAC-PapersOnLine, Volume 59, Issue 10, 2025, Pages 1372-1377, ISSN 2405-8963
This paper presents a novel approach to integrated manufacturing-microgrid control using multi-agent deep reinforcement learning. We address the fundamental challenges of coordinating production schedules with variable renewable energy sources through a distributed control framework based on Partially Observable Markov Decision Process (POMDP).
Enhancing Control in Manufacturing and Microgrid Systems: Deep Reinforcement Learning with Double Q-Learning
2023 14th International Conference on Intelligent Systems: Theories and Applications (SITA), Casablanca, Morocco, pp. 1-7
This research presents an advanced approach to manufacturing and microgrid control systems using deep reinforcement learning with double Q-learning techniques. The study addresses the challenges of coordinating industrial operations with energy management systems to achieve optimal performance and efficiency.
Forecasting Call Center Arrivals Using Machine Learning
Osmaniye Korkut Ata University Journal of Natural and Applied Sciences, Year 2021, Volume: 4 Issue: 1, pp. 96-101
A call center is an office equipped to handle a large volume of telephone calls for an organization, for which the ability to forecast calls is a key factor. By forecasting the number of calls accurately, a company can plan staffing needs, meet service level requirements, improve customer satisfaction and benefit from many other optimizations. In this paper, we develop Multilayer Perceptron (MLP) and Long-Short Term Memory (LSTM) based models combined with time lags to forecast the number of call arrivals in a call center. We forecast 12, 24, 36 and 48 values ahead and the performance of the forecasting models has been evaluated using the Mean Absolute Error (MAE). The MLP based model results show that the MAE values change between 1,50 and 13,58 and LSTM based model results show that the MAE values change between 19,99 and 66,74.
Education
PhD Candidate
Data Science and Machine Learning
INPT, Rabat
Jan 2023 - Present
Engineering Degree
Computer Science
INPT, Rabat
Sept 2016 - Dec 2019
Exchange Semester
Computer Engineering
ÇUKUROVA University, Turkey
Sept 2018 - Feb 2019
Languages
Native
Proficient
Professional Certifications
Industry-recognized credentials and achievements
Azure AI Engineer Associate
Microsoft
Certified in designing and implementing AI solutions using Azure Cognitive Services, Azure Machine Learning, and Knowledge Mining.
Machine Learning Specialist
AWS
Expert-level certification in designing, implementing, deploying, and maintaining machine learning solutions on AWS.
Professional Machine Learning Engineer
Google Cloud
Certified in designing, building, and productionizing ML models to solve business challenges using Google Cloud technologies.
TensorFlow Developer
TensorFlow
Demonstrated proficiency in using TensorFlow to solve deep learning and ML problems across computer vision, NLP, and time series.
Deep Learning Specialization
Coursera - DeepLearning.AI
Comprehensive specialization covering neural networks, CNNs, RNNs, and advanced deep learning techniques and architectures.
Natural Language Processing
Coursera - DeepLearning.AI
Specialized certification in NLP techniques, transformers, attention mechanisms, and modern language model architectures.
Get In Touch
Let's Connect
I'm always interested in discussing new opportunities, AI projects, or potential collaborations. Feel free to reach out!