AI/ML Engineer with hands-on experience building and deploying production-grade NLP, LLM, and computer vision systems. Specialized in multi-task learning, emotion-aware AI, and Retrieval-Augmented Generation (RAG). Prove…
AI/ML Engineer with hands-on experience building and deploying production-grade NLP, LLM, and computer vision systems. Specialized in multi-task learning, emotion-aware AI, and Retrieval-Augmented Generation (RAG). Proven ability to design scalable FastAPI, Express, Nest, and microservices-based backends, integrate transformer models into real-world applications, and deliver end-to-end AI solutions using PyTorch, TensorFlow, and modern MLOps practices
Built a Hybrid RAG pipeline (LangChain/LangGraph), improving retrieval precision by 40%.
Reduced LLM hallucinations by 30% via robust document parsing and chunking.
Deployed local T5 inference for secure, API-free NLP processing.
Engineered multi-agent GenAI pipelines for bulk content generation, reducing manual entry time by ~70% and processing 10,000 assets weekly.
Developed multiple ML-powered Chrome extensions to automate dynamic web scraping, improving extraction reliability by 90% over legacy scripts.
Architected a real-time multi-vendor platform with secure payments and WebSockets, supporting 1000 concurrent users with sub-second latency.
Engineered multi-agent GenAI pipelines for bulk content generation, reducing manual entry time by ~70% and processing 10,000 assets weekly.Developed multiple ML-powered Chrome extensions to automate dynamic web scraping, improving extraction reliability by 90% over legacy scripts.Architected a real-time multi-vendor platform with secure payments and WebSockets, supporting 1000 concurrent users with sub-second latency
Fine-tuned YOLO architectures (v5) for custom object detection, increasing Mean Average Precision (mAP) by 20-30% through rigorous hyperparameter optimization.Conducted Exploratory Data Analysis (EDA) on 1,000+ images to identify class imbalances, implementing augmentation strategies that reduced edge-case prediction failures by 30%.Collaborated on deployments, reducing inference time by 30% through optimization techniques.
Developed and optimized REST APIs for a microservices e-commerce platform, reducing average endpoint response time by ~30% through efficient database query indexing.
Diagnosed and resolved critical data flow bottlenecks between services, eliminating cross-service timeouts and improving data synchronization accuracy to 99%.
Enhanced system reliability under high load (5,000+ daily requests) by implementing Redis caching, which reduced core database load by approximately 40%.
Developed and optimized REST APIs for a microservices e-commerce platform, reducing average endpoint response time by ~30% through efficient database query indexing.Diagnosed and resolved critical data flow bottlenecks between services, eliminating cross-service timeouts and improving data synchronization accuracy to 99%.Enhanced system reliability under high load (5,000+ daily requests) by implementing Redis caching, which reduced core database load by approximately 40%.
نظام التوظيف التشغيلي المعتمد على الذكاء الاصطناعي أولاً، الذي يوحّد ويؤتمت دورة التوظيف بالكامل للمؤسسات الحديثة حول العالم.
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