Junior AI & Machine Learning Engineer · Mansoura, Egypt
About
Junior AI & Machine Learning Engineer with hands-on experience in Generative AI, Agentic Workflows, Computer Vision, and Full-Stack AI Integration. Passionate about building scalable, production-ready AI solutions and continuously developing expertise in applied AI/ML systems.
Experience
Agentic & Generative AI Trainee — Digital Egypt Pioneers Initiative (DEPI)
Architected and implemented autonomous agent workflows, tool-calling harnesses, and context management protocols (MCP) using Python.
Designed and deployed semantic RAG pipelines using ChromaDB and vector search for high-accuracy contextual retrieval.
Built automated integration workflows connecting REST APIs and webhooks using n8n and FastAPI to eliminate execution failure modes.
Leveraged agentic coding environments (Cursor, Claude Code) to prototype, test, and ship production-grade software prototypes.
Artificial Intelligence Intern — Decode Labs
Developed and fine-tuned machine learning and deep learning models using Python, PyTorch, and Scikit-learn.
Optimized computer vision and NLP pipelines to reduce inference latency and enhance accuracy on production workloads.
Containerized AI microservices using Docker and integrated model endpoints into production-ready backends with FastAPI.
Collaborated with engineering teams on automated data preprocessing, pipeline evaluation, and deployment documentation.
AI & Machine Learning Summer Intern — Microsoft & Sprints
Built and evaluated predictive machine learning models using Python, Scikit-learn, and Pandas.
Performed feature engineering, data cleaning, and exploratory data analysis across structured and unstructured datasets.
Developed interactive frontend dashboards with React and REST APIs to serve ML model inferences to end-users.
Built a full-stack automated platform converting unstructured documents into structured quizzes and video lessons in under 2 minutes.
Implemented end-to-end RAG pipelines using ChromaDB for semantic retrieval and context synthesis.
Developed scalable RESTful backend services using FastAPI and an interactive responsive UI using Next.js.
Developed an autonomous aquatic debris detection system using custom-trained YOLOv8 object detection models.
Deployed real-time embedded computer vision inference connected to an ESP32 microcontroller for telemetry and hardware navigation.
Integrated low-latency communication protocols for live field monitoring and automated waste sorting.
Built a hybrid CNN-LSTM neural network architecture to perform temporal sequence classification on American Sign Language video streams.
Implemented real-time video frame preprocessing and data augmentation pipelines, achieving high recognition accuracy.
Engineered a motion tracking system analyzing tri-axial accelerometer streams to detect elderly falls in real time.
Trained a Random Forest classification model integrated with a Flask REST API backend for alert triggering.
