EMEman
AboutSelected workExperiencePracticeCredentialsContact
Eman
  • 01About
  • 02Selected work
  • 03Experience
  • 04Practice
  • 05Credentials
  • 06Contact
emanelshbiny@gmail.com

Eman Mahmoud ELshbiny

AI/ML Engineer

Based
Cairo, Egypt
Status
Available for work

Innovative AI/ML Engineer specializing in Generative AI, RAG architectures, and workflow automation.

01—About

Eman Mahmoud ELshbiny
Portrait— Eman Mahmoud ELshbiny

AI/ML Engineer

As a highly motivated and innovative AI/ML Engineer, I specialize in developing end-to-end intelligent applications using Generative AI, RAG architectures, and workflow automation. With a strong foundation in deep learning frameworks and advanced skills in infrastructure automation and workflow tools, I enable the deployment of scalable, production-ready AI solutions. My expertise includes Predictive Modeling, Regression, Classification, Deep Learning, and Automation & Infrastructure.

02—Selected work

№ 01

Network Traffic Forecasting & Trend Analysis

Developed and trained predictive Machine Learning models (such as Regression or LSTM/ Time-Series models) to forecast network traffic congestion.

Python · TensorFlow · PyTorch

№ 02

AI Shopping Assistant for SHEOUT

Engineered a production-ready RAG chatbot using Python and Streamlit to query clothing store inventory in real-time.

Python · Streamlit · Gemini

№ 03

Ports of Future (Nokia)

Analyzed real-time IoT and sensor streaming data to optimize operational efficiency and predict safety risks in port environments.

Python · TensorFlow · PyTorch

03—Experience

  1. 2020 — 2025

    Graduation Project: Medical ApplicationFaculty Of Engineering AL Azhar University

    Database Design & Querying: Designed the relational database schema to handle user profiles, ratings, and doctor specializations efficiently using SQL. Implemented data filtering and advanced query logic to enable real-time sorting based on ratings, reviews, and proximity data.

  2. Real-Time Data AnalysisPorts of Future (Nokia)

    Analyzed real-time IoT and sensor streaming data to optimize operational efficiency and predict safety risks in port environments. Leveraged data-driven virtual modeling (Digital Twins) to evaluate and simulate port traffic and trade logistics performance.

  3. Engineered a production-ready RAG chatbotAI Shopping Assistant for SHEOUT

    Engineered a production-ready RAG chatbot using Python and Streamlit to query clothing store inventory in real-time. Integrated advanced LLMs (Gemini) to deliver fast, context-aware, and natural language responses.

  4. Developed and trained predictive Machine Learning modelsNetwork Traffic Forecasting & Trend Analysis

    Developed and trained predictive Machine Learning models (such as Regression or LSTM/ Time-Series models) to forecast network traffic congestion. Feature Engineering: Extracted high-impact temporal features from raw network data using Python to improve model learning and predictive accuracy.

04—Practice

Tools & craft

Generative AI & LLMs·
RAG Architecture·
Machine Learning & AI·
Programming & Scripting·
Frameworks & Libraries·
Data base·
Automation & Infrastructure·
Data Analysis & Visualization·
Telecom & Networking·
Office

05—Credentials

Education

  • 2020 — 2025

    Diploma, Mobile Network Automation

    Faculty Of Engineering AL Azhar University

    Graduation Project: Medical Application (Grade: Excellent)

  • HireReady-DEY, Mobile Network Automation

    National Telecommunication Institute (NTI)

Certifications

  • Generative AI Literacy

    SkillQuest · 04/2026

  • Ansible Automation-Red Hat

    02/2026

  • HCIA_AI

    01/2026

  • HCCDA AI

    01/2026

  • Mobile Network Automation - NTI

    National Telecommunication Institute (NTI) · 10/2025 – 01/2026

  • Mobile Network - Nokia

    Nokia · 08/2025

  • ITI Training: FRONT-END, HTML and CSS.

    2022

06—Contact

Get in touch

Have something in mind? Let's talk.

  • Emailemanelshbiny@gmail.com
  • Phone01005047845
  • LocationCairo, Egypt

© 2026 Eman Mahmoud ELshbiny.

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