Layth Ayache
AI Engineer | Computer Vision & NLP | Product Builder
Building end-to-end ML pipelines that ship. Specializing in Computer Vision, NLP, and mobile integration—with a focus on Arabic/Lebanese contexts and real-world constraints.
End-to-End ML Pipelines
From data collection to deployment, building production-ready ML systems
CV/NLP + Mobile Integration
Bridging computer vision, NLP, and mobile platforms for accessible solutions
Applied Research & Reporting
Technical writing, structured analysis, and measurable outcomes
Product-Minded Engineering
Entrepreneurial thinking: pricing, deployment, iteration, stakeholder alignment
About
Building AI systems that solve real problems
What I Do
I specialize in building end-to-end AI and ML systems, with a focus on Computer Vision and Natural Language Processing. My work spans from research and experimentation to production deployment, always considering real-world constraints and practical implementation challenges.
I have particular expertise in Arabic and Lebanese contexts, building solutions that work with under-resourced languages and regional data challenges. My projects range from sign language translation systems to fashion trend detection, housing price prediction, and retail analytics—each demonstrating a commitment to shipping working products.
How I Work
I approach projects with a structured, iterative methodology. Every system I build starts with clear problem definition, followed by systematic exploration of approaches, rigorous evaluation, and continuous iteration based on feedback.
I believe in measurable outcomes and clear documentation. Whether it's a research project or a production system, I ensure that decisions are data-driven, results are reproducible, and the work is well-documented for future reference.
Where I'm Heading
I'm actively seeking roles in AI Engineering, ML Engineering, Computer Vision, and Data Analysis—with a focus on opportunities in the Gulf region and remote positions. I'm particularly interested in roles that combine technical depth with product ownership, where I can contribute to both the technical architecture and the strategic direction.
I'm open to collaborations, consulting opportunities, and full-time positions that allow me to work on meaningful problems with measurable impact. If you're building something interesting in AI/ML, I'd love to hear about it.
Skills
Technical expertise across the ML stack
AI/ML
- • PyTorch
- • TensorFlow
- • Scikit-learn
- • Machine Learning
- • Deep Learning
- • Model Training & Evaluation
Computer Vision
- • Image Processing
- • Object Detection
- • Image Classification
- • Feature Extraction
- • CV Pipelines
NLP / Arabic Dialects
- • Natural Language Processing
- • Arabic NLP
- • Text Analysis
- • Language Models
- • Multilingual Systems
Data
- • Pandas
- • NumPy
- • Data Visualization
- • Statistical Analysis
- • Data Pipelines
- • Feature Engineering
Backend & APIs
- • Python
- • REST APIs
- • Microservices
- • System Design
- • API Integration
Mobile & Integration
- • Android Development
- • Mobile Integration
- • Cross-platform Development
DevOps/Cloud
- • Cloud Deployment
- • CI/CD Basics
- • Containerization
- • Version Control
Cyber/Networking
- • Network Security
- • Security Analysis
- • Ethical Research
Projects
End-to-end ML systems and product builds
Multilingual sign language translation focusing on Lebanese Sign Language using CV, NLP, and mobile integration
Problem:
Limited accessibility tools for Lebanese Sign Language speakers, with existing solutions lacking proper CV+NLP integration for real-time translation.
Approach:
Built a pipeline combining computer vision for sign recognition, NLP for language processing, and Android integration for mobile deployment. Focused on Lebanese Sign Language as primary target with extensibility to other dialects.
Result:
Delivered a working prototype demonstrating real-time sign language recognition and translation, with mobile-first architecture enabling offline capabilities and improved accessibility.
Python-based ML system for analyzing and predicting fashion trends from visual data
Problem:
Fashion retailers need data-driven insights into emerging trends, but manual analysis is time-consuming and subjective.
Approach:
Developed a computer vision pipeline to analyze fashion imagery, extract style features, and identify trend patterns. Implemented clustering and classification models to categorize and predict trend evolution.
Result:
Created a scalable system capable of processing large volumes of fashion imagery and generating trend insights, with potential applications in inventory planning and marketing strategy.
End-to-end ML pipeline for predicting housing prices with feature engineering and model optimization
Problem:
Real estate pricing requires accurate predictions based on multiple features, but existing models lack proper feature engineering and validation.
Approach:
Built a comprehensive regression pipeline with feature engineering, data preprocessing, model selection (tried multiple algorithms), and cross-validation. Focused on interpretability and model performance metrics.
Result:
Achieved improved prediction accuracy compared to baseline models, with a production-ready pipeline that can be extended with additional data sources.
K-means and hierarchical clustering for customer segmentation in retail
Problem:
Retail businesses need to understand customer segments for targeted marketing, but lack automated segmentation tools.
Approach:
Implemented both K-means and hierarchical clustering algorithms to segment customers based on purchasing behavior. Compared approaches and selected optimal clustering parameters. Created visualizations for interpretability.
Result:
Identified distinct customer segments with actionable insights, enabling targeted marketing strategies. Demonstrated the trade-offs between different clustering approaches.
Product-focused automation system with AI chatbot integration for business communication
Problem:
Small businesses need automated customer communication but existing solutions are expensive or lack customization for Arabic/Lebanese contexts.
Approach:
Designed and built an automation system integrating WhatsApp API with an AI-powered chatbot. Focused on Arabic language support, pricing models, and deployment architecture. Iterated based on user feedback.
Result:
Delivered a working prototype with Arabic language capabilities, demonstrating product thinking around pricing, deployment, and user experience. System ready for scaling with proper infrastructure.
Scalable microservice architecture for computer vision analysis with live interview Q&A capabilities
Problem:
Organizations need scalable CV analysis tools, but monolithic solutions lack flexibility and real-time capabilities.
Approach:
Architected a microservice-based system for CV analysis with separate services for image processing, feature extraction, and Q&A. Designed for horizontal scaling and API-first approach. Included live interview Q&A as a use case.
Result:
Built a production-ready microservice architecture demonstrating system design principles, with APIs ready for integration. Showed understanding of cloud deployment and DevOps practices.
Ethical security research and network analysis tools for understanding system vulnerabilities
Problem:
Understanding network security requires hands-on experience with analysis tools and vulnerability assessment in controlled environments.
Approach:
Developed a lab environment for network security analysis, focusing on ethical research practices. Built tools for network traffic analysis, vulnerability scanning, and security reporting. Emphasized responsible disclosure and educational use.
Result:
Created a comprehensive security analysis toolkit demonstrating understanding of networking, cybersecurity principles, and ethical research practices. All work conducted in controlled, educational environments.
Data pipeline for automated report generation with visualization dashboard
Problem:
Organizations need automated reporting but manual processes are error-prone and time-consuming.
Approach:
Built an end-to-end data pipeline that collects, processes, and visualizes data with automated report generation. Focused on structured reporting, measurable metrics, and stakeholder-friendly outputs.
Result:
Delivered a working system that automates report generation, reducing manual effort and improving consistency. Dashboard provides real-time insights for decision-making.
Selected Work & Leadership
Building products and delivering results
Product Builder / Independent Projects
Freelance & Personal Projects
- •Built end-to-end ML products from concept to deployment, including Lebanese Sign Language translation system, fashion trend detection, and automation tools.
- •Designed pricing models, deployment strategies, and iteration cycles based on user feedback and market needs.
- •Demonstrated ownership across the full product lifecycle: requirements gathering, system design, implementation, testing, and deployment.
Research Writing & Technical Reporting
Academic & Professional
- •Produced structured technical reports and research documentation for ML projects, including literature reviews, methodology documentation, and results analysis.
- •Wrote clear, actionable documentation that bridges technical depth with stakeholder communication.
- •Created reproducible research workflows with proper version control and documentation practices.
Team Collaboration & Delivery
Project-Based Teams
- •Collaborated on cross-functional teams to deliver ML projects, managing requirements, timelines, and stakeholder expectations.
- •Practiced iterative development with regular feedback loops and measurable outcomes.
- •Led technical discussions and contributed to architecture decisions, balancing technical excellence with practical constraints.
Writing & Research
Technical notes, research reviews, and documentation
AI/ML Applications in Healthcare: A Literature Review
ReviewComprehensive survey of current AI/ML applications in healthcare, covering computer vision for medical imaging, NLP for clinical notes, and predictive modeling. Focus on practical implementations and challenges.
Sign Language Recognition: Technical Approaches and Challenges
ArticleTechnical deep-dive into sign language recognition systems, comparing CV approaches, discussing data collection challenges, and exploring mobile deployment strategies. Focus on under-resourced languages.
End-to-End ML Pipeline Documentation
DocumentationStructured documentation for building production ML pipelines, covering data collection, preprocessing, model training, evaluation, and deployment. Includes best practices and common pitfalls.
Arabic NLP: Challenges and Opportunities
ArticleAnalysis of Arabic NLP challenges including dialectal variation, script complexity, and resource scarcity. Discussion of practical approaches for Arabic language processing in real-world applications.
Get in Touch
Open to opportunities, collaborations, and interesting problems
I'm actively seeking roles in AI Engineering, Computer Vision, NLP, and Data Analysis—with a focus on opportunities in the Gulf region and remote positions. I'm also open to collaborations, consulting opportunities, and discussions about interesting problems in AI/ML.
What I'm Open To
- • AI Engineer / ML Engineer roles (Gulf-focused or remote)
- • Computer Vision & NLP positions
- • Data Analyst / Data Scientist opportunities
- • Product-focused engineering roles
- • Research collaborations
- • Consulting and freelance projects