Mousa Alagha
AI EngineerAI is analyzing your overall score…
Identifying your key strengths…
Evaluating your skill match against the job requirements…
Assessing your cultural and operational fit
AI is analyzing your overall score…
Identifying your key strengths…
Evaluating your skill match against the job requirements…
Assessing your cultural and operational fit
AI Engineer with less than a year in Machine Learning & Computer Vision, specialized in deploying pr
AI/ML engineer with hands-on experience building and deploying production machine-learning systems end to end, from model development and optimization through containerized deployment, monitoring, and field testing. Strong in Python and deep learning (TensorFlow, TensorFlow Lite, PyTorch, Scikit-learn, OpenCV, CNNs), with a proven record of operationalizing AI at scale (20+ edge devices in live operation) and integrating models into applications via REST/FastAPI, Docker, and Git-based workflows. A fast learner with hands-on generative-AI experience, including a retrieval-augmented generation (RAG) chatbot built on an open-source LLM and FAISS, who collaborates well across diverse, fast-moving teams; UAE Golden Visa holder in Abu Dhabi, fluent in English. Now seeking an AI/ML Engineering role to design, deploy, and scale intelligent platforms, including conversational AI and enterprise automation, across cloud and on-prem infrastructure.
Abu Dhabi University
Bachelor of Science · Computer Engineering
June 1, 2021 – September 1, 2025
SULMI
Embedded Systems / AI Engineering Intern
April 1, 2026 – Present
India
ADNOC Offshore
Computer Engineering Intern
June 1, 2025 – August 1, 2025
India
Low-Cost AI-Enabled Student Engagement Monitoring System
July 1, 2025 – July 1, 2025
Developed a real-time computer-vision video-analytics system using Python, OpenCV, TensorFlow Lite, Raspberry Pi, and Firebase to detect students' engagement states from live camera feeds in classroom environments. Built and validated 20 deployed devices for full-day classroom operation, enabling video capture, on-device inference, human-readable status logging, and cloud synchronization on low-cost hardware.
Raspberry Pi Lane Assist Mini Autonomous Car
January 1, 2025 – January 1, 2025
Implemented a lane-detection and control pipeline on Raspberry Pi using perspective transform, thresholding, edge/line detection, and PID steering. Achieved stable lane tracking across varied layouts with responsive steering control and quick recovery from lane deviations.
AI-Powered Exercise Recognition Glove
January 1, 2025 – January 1, 2025
Built an exercise-recognition glove on Arduino Nano 33 BLE Sense using IMU data and TensorFlow Lite to classify 5+ movements in real time Enabled stable on-device repetition counting with immediate buzzer/LED feedback for interactive exercise monitoring.
Engineer License
DMT Abu Dhabi
June 1, 2026 – Present
Edge AI Fundamentals Certificate
Edge Impulse
June 1, 2026 – Present
Evolution of Edge AI & Use Cases
Qualcomm Academy
June 1, 2026 – Present
Introduction to Generative AI
June 1, 2026 – Present
Introduction to IoT
Cisco Networking Academy
June 1, 2026 – Present
Cultural Fit Analysis
The candidate's academic projects demonstrate initiative and a strong interest in applying AI to real-world problems, particularly in embedded and edge contexts. The internships, especially the one at ADNOC Offshore, show an ability to adapt to industrial environments and learn operational standards. The diverse range of certifications indicates a proactive and self-driven learning approach. The target role of 'AI Engineer' aligns well with the candidate's demonstrated skills and project focus on deploying AI systems end-to-end. The current internship in Embedded Systems/AI Engineering further strengthens this alignment. However, the experience level is still early career, which might require mentorship in a senior role.
Soft Skills & Operational Fit
The candidate's project descriptions and internship experiences suggest an ability to work in structured environments and collaborate within technical teams. The objective statement highlights a desire to collaborate across diverse, fast-moving teams. The experience in troubleshooting hardware faults indicates problem-solving skills. However, without direct interview data, a comprehensive assessment of soft skills like leadership, conflict resolution, or advanced communication is not possible.