AI Engineer

Open to full-time

Bio

Amr M. is an AI Engineer with several years of experience specializing in MLOps and Cloud-Native AI. Amr utilizes technologies such as Python, FastAPI, TensorFlow, PyTorch, and Scikit-learn to build scalable ML pipelines, REST APIs, and enterprise-level conversational agents. He implements CI/CD with GitHub Actions and Docker, and manages cloud infrastructure using AWS services like EC2, S3, and RDS. His work emphasizes secure deployment, experiment tracking, and performance optimization. At Elevvo, Amr built and optimized over six ML models, enhancing accuracy by 10–25% and improving performance by up to 30% through techniques like SMOTE and Transfer Learning. He also developed the DocuMind platform, a Retrieval Augmented Generation system, enabling semantic search over unstructured data and automating deployment pipelines. Amr holds a Bachelor of Computer Science from Ain Shams University. He is well-suited for roles focusing on AI model deployment, cloud infrastructure management, and advanced MLOps practices.

Expertise

PythonFast APISQLAWSPyTorchNumPy

Video Intro

Assessments

General Project Assessment

(80/100)

Great on Count Subarrays with Sum Equal to KEasy
Great on Classification Model InaccuracyEasy
Great on Diagnose and Fix RAG Pipeline Retrieval IssuesMedium

Projects

DocuMind: Enterprise RAG Platform with MLOps

Developed a Retrieval Augmented Generation (RAG) system using LangChain and ChromaDB to enable semantic search over unstructured corporate data. Orchestrated data versioning pipelines using DVC synced with AWS S3, and implemented MLflow to track prompt engineering experiments and embedding performance. Built a fully automated deployment pipeline using GitHub Actions and Docker; commits trigger automated Pytest suites and seamless deployment to AWS EC2. Engineered high-performance Async APIs using FastAPI to handle concurrent document ingestion, chunking, and vector retrieval.

BeanBuddy: Cloud-Native Transactional AI

Architected a stateful conversational agent using Dialogflow ES and FastAPI, handling complex transactional workflows (ordering, modifications). Migrated persistence layers to a production-grade MySQL database on AWS RDS, managing schema design and session integrity. Deployed infrastructure on AWS EC2 (Linux), managing persistent background processes using Screen and implementing Ngrok tunneling for secure SSL communication.

Experience

AI Engineer Intern
Elevvo· AI/MLJul 2025 — Sep 2025
- Built and tuned 6+ ML models (Regression, Classification, CNNs) using SMOTE and hyperparameter optimization, improving accuracy by 10–25%.
- Designed reproducible ML pipelines for preprocessing and feature engineering, integrating MLflow for experiment tracking and versioning.
- Improved model performance by up to 30% using SVD and Transfer Learning.