Bosy Ayman
Software 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
Software Engineer with less than a year in Machine Learning & AI
Bosy Ayman is an aspiring Software Engineer specializing in Data Science and Artificial Intelligence, with hands-on experience in developing intelligent systems and data infrastructure. With a strong foundation in Python, Machine Learning, Deep Learning, and Computer Vision, she has contributed to projects like an AI-powered video analytics platform and an incident management system. Her skills extend to various frameworks and technologies, including Flask, React, PyTorch, TensorFlow Lite, and PostgreSQL, demonstrating a versatile and data-driven approach to software development. Currently pursuing a B.Sc. in Computer Science, Bosy is poised to excel in roles requiring innovative AI/ML solutions and robust system development.
Zewail City of Science and Technology
B.Sc. · Computer Science Major: Data Science and Artificial Intelligence
September 1, 2022 – June 1, 2026
Al Nas Hospital
Software Development Intern
August 1, 2025 – September 1, 2025
India
Cairo International Airport
Internship Trainee
August 1, 2025 – August 1, 2025
India
Brain-Tumor Classification
June 1, 2026 – Present
Classified MRI brain tumor images into 4 categories using MobileNetV2; optimized with meta-heuristic algorithms and visualized with Grad-CAM.
RawiVision Intelligent Video Analytics Platform
June 1, 2026 – Present
Developed an on-premise AI-powered surveillance platform for real-time video analytics, combining live monitoring, employee attendance tracking, anomaly detection, semantic search, and video summarization. Implemented person detection and multi-object tracking with YOLOv8 and StrongSORT, and integrated FaceNet-based facial recognition to automate employee check-in and check-out from RTSP camera feeds. Built a two-stage anomaly detection pipeline using VideoMAE for spatiotemporal event screening and SmolVLM for concise natural-language incident descriptions and dashboard alerts. Designed semantic video search and summarization workflows using pgvector, MinIO, Celery, and RabbitMQ to index footage, retrieve relevant clips, and generate concise reviewable summaries while keeping all data on-premise.
Blind Navigation Mobile App
June 1, 2026 – Present
Developed a real-time Android app to assist visually impaired users with indoor navigation. Used YOLOv8 model for object detection and provided audio feedback for mobility support.
BERT-based Chatbot
June 1, 2026 – Present
Developed an NLP chatbot for question answering with model training, evaluation, and deployment.
FitHub Web Application
June 1, 2026 – Present
Created a fitness platform with secure online payments and admin dashboard for trainers and users.
Data Visualization
Coursera
June 1, 2026 – Present
Supervised Machine Learning (Andrew Ng)
Coursera
June 1, 2026 – Present
DELF A2-B1
French Ministry of Education
June 1, 2026 – Present
1st Place – Girls' Chess Tournament
Nile University
June 1, 2026 – Present
Cultural Fit Analysis
The candidate's academic background and project diversity, particularly in AI/ML, align well with a technically driven culture. Involvement in extracurriculars and leadership roles suggests a proactive and engaged individual. However, the limited professional experience means their adaptability to specific corporate cultural nuances and established engineering processes is yet to be fully demonstrated.
Soft Skills & Operational Fit
The candidate demonstrates initiative and leadership through extracurricular activities like leading the Chess Club. Project descriptions indicate an ability to work on complex, multi-component systems. However, the experience is primarily academic and internship-based, suggesting a need for further development in professional operational contexts and large-scale team collaboration.