EXPERIENCE.

A journey through my professional career in AI, Machine Learning, and Software Engineering.

Full-Stack AI Engineer

Royal Hashemite Court

Aug 2024 – Present

Architecting and deploying end-to-end Machine Learning and Generative AI systems in highly confidential, air-gapped environments. Responsible for the complete production lifecycle from bare-metal infrastructure optimization to advanced AI agent development.

/Architected Secure GenAI Systems: Designed on-prem RAG & Agentic AI platforms using vLLM for high-performance inference.
/Engineered Autonomous AI Agents: Developed agents with tool-calling, long-term memory, and strict validation layers for document intelligence.
/Advanced Computer Vision: Built real-time pipelines for Detection, Tracking, and Pose Estimation via WebSockets/WebRTC.
/Cyber-Physical Integration: Orchestrated real-time perception for autonomous platforms using LiDAR, RGB sensors, and NVIDIA Jetson.
/High-Scale MLOps: Directed bare-metal AI data center setups and orchestrated microservices using Docker Swarm with Prometheus/Grafana.
/Multi-Modal Data Architecture: Designed hybrid systems using PostgreSQL, MongoDB, and Vector Databases (Qdrant/Milvus).

Generative AILLMsRAGComputer VisionMLOpsDocker SwarmvLLMVector DatabasesFastAPI

Machine Learning Engineer

Nafith Logistics International

July 2023 – Aug 2024

Spearheaded the full production pipeline for proprietary computer vision models in the logistics sector, focusing on real-time streaming infrastructure and distributed MLOps workflows.

/End-to-End ML Lifecycle: Managed automated data collection, annotation, custom PyTorch training, and edge deployment.
/Industrial ML Pipelines: Deployed solutions for automated object detection, tracking, and counting for high-volume cargo.
/Real-Time Streaming: Developed high-throughput pipelines using Kafka, GStreamer, and WebSockets for live telemetry.
/Advanced Image Processing: Applied image stitching and 3D processing to enhance spatial accuracy in logistics.
/Distributed MLOps: Implemented workflows using Docker Swarm to manage microservices across edge deployments.
/Infrastructure Optimization: Tuned high-performance GPU environments using CUDA and cuDNN.

Computer VisionPyTorchKafkaGStreamerDocker SwarmCUDA3D Image Processing

Data Science Intern

SHAI FOR AI

Sep 2022 - Dec 2022

Completed an intensive internship focusing on data science and software engineering, delivering high-quality work across multiple large-scale AI projects.

/Computer Vision: Developed a Playing Card Detection system and built a Tarneeb game engine based on model detections.
/NLP & Search: Built a functional search engine project utilizing natural language processing techniques.
/Predictive Modeling: Developed a PUBG Finish Placement Prediction project using ML, Deep Learning, and EDA.
/Software Engineering: Collaborated on a Library management project using OOP, clean code principles, and Git.
/Technical Communication: Conducted regular presentations to discuss results, processes, and technical methodologies.

Data ScienceNLPMachine LearningDeep LearningOOPPythonGit