Mohammed M.

Key Skills

Software

Other

Top Subject Matter

Nlp Domain Expertise

Transformers Domain Expertise

Rag Domain Expertise

Top Data Types

Text

Document

Top Task Types

Fine-tuning

Prompt + Response Writing (SFT)

Question Answering

Freelancer Overview

NLP Trainee at Applai (AI training-focused coursework). Brings 2+ years of professional experience across complex professional workflows, research, and quality-focused execution. Core strengths include Other. Education includes Bachelor of Science, Ain Shams University (2026). AI-training focus includes data types such as Computer Code, Programming, and Text and labeling workflows including Fine-tuning, Prompt + Response Writing (SFT), and Question Answering.

Labeling Experience

TestMate graduation project (LLM fine-tuning and evaluation for test scaffolding)

OtherFine-tuning

Mohammed developed an autonomous agentic testing framework that combines graph-based context extraction with LLM-driven semantic reasoning. He fine-tuned an open-source code model using 4-bit quantized LoRA/PEFT and trained with a rejection sampling pipeline on custom Python datasets. The system also used post-run auditing to evaluate generated behaviors and isolate real defects from LLM hallucinations. • Fine-tuned Qwen2.5-Coder-7B with 4-bit LoRA/PEFT • Applied rejection sampling to improve training outcomes • Built a three-gate post-run audit pipeline (syntax validation, pytest flakiness detection, behavioral incoherence mapping) • Evaluated performance on a benchmark using mutation score and line coverage

2025 - Present

AI-Powered Root Cause Analyzer project (RAG-based AI training/feedback workflow)

OtherDocumentQuestion Answering

Mohammed developed a RAG pipeline to power automated root cause analysis from incident records. The pipeline ingests incident documents, retrieves relevant context semantically, and uses the retrieved information to generate analysis. A human-in-the-loop feedback mechanism and analyst-facing UI were included to support iterative improvement. • Ingested and semantically retrieved incident records with a RAG pipeline • Generated root cause analysis using Gemini 2.5 Flash • Implemented FastAPI backend with human-in-the-loop feedback • Built a real-time dashboard for incident querying and analyst review

2025 - 2025

AI-Powered Internship Tracker project (LLM/NLP coaching-style feedback)

OtherTextPrompt + Response Writing (SFT)

Mohammed built an AI-powered internship tracker that uses NLP techniques to parse resumes and tailor interview feedback. The project used semantic preprocessing and information extraction from resume text to support downstream job matching and coaching-style feedback. It served as an end-to-end data processing and response generation workflow. • Resume parsing with spaCy • Job matching using TF-IDF • Tailored interview feedback generation • Implemented a Streamlit interface for interactive use

2025 - 2025

NLP Trainee at Applai (AI training-focused coursework)

OtherFine-tuning

Mohammed Medhat Abd Alim completed structured NLP trainee training involving AI training and fine-tuning concepts for Transformer-based and RAG/agentic systems. The experience included learning how to build and apply LLM pipelines for semantic retrieval and agent workflows using modern deep learning toolchains. It culminated in knowledge sharing through a public presentation on Transformer architecture. • Training on Transformers, RAG, Agents, and Fine-Tuning • Practical exposure to LLM-related pipeline concepts • Public session delivered on Transformer architecture • Reinforced model training workflow understanding

2024 - 2024

Education

Work History