MOHAMED SHIBILY THOTTOLI

AI & Data Science Engineer | Machine Learning | Python

+91 9074134200 [email protected]

Resume

Hello, I am

MOHAMED SHIBILY THOTTOLI.

1

GenAI Project

1

Machine Learning Project

About Me

I am a B.Tech graduate (2026) in Artificial Intelligence and Data Science with a strong interest in building practical, data-driven solutions. My hands-on skills span Python, SQL, Machine Learning, Deep Learning, Natural Language Processing (NLP), Generative AI, and Agentic AI, developed through continuous project-based learning.

I enjoy solving problems, exploring new technologies, and understanding how AI can create meaningful real-world impact. My project work has strengthened my analytical thinking and my ability to learn and adapt quickly.

I am currently seeking entry-level AI Engineer, Machine Learning Engineer, and Data Scientist roles where I can apply my technical knowledge, contribute to impactful projects, and keep growing as an AI and data professional.

Key Skills

Python

SQL

Machine Learning

Deep Learning

Data Science

Data Analytics

Generative AI

LLMs

Prompt Engineering

RAG

LangChain

AI Agents

Hugging Face Transformers

PyTorch

Scikit-learn

Pandas

NumPy

NLP

Computer Vision

CNN

Transfer Learning

OpenCV

ChromaDB

Streamlit

FastAPI

React.js

REST APIs

Vector Databases

Semantic Search

Text Summarization

Speech-to-Text

Feature Engineering

EDA

Data Visualization

Model Evaluation

Git

GitHub

MLflow

DagsHub

Gemini API

Llama Models

Whisper

CrewAI

MCP

Business Analytics

Jupyter Notebook

My Projects

My Experience

Data Scientist Intern | Internship
AtliQ Technologies | Aug 2026 – Sep 2026 | Remote

Processed and cleaned 75,000+ records, improving dataset quality scores by 28% and accelerating downstream analytics workflows.
Built a CNN-based transfer learning model achieving 96.2% accuracy across 7 fruit classes, improving defect identification reliability.
Engineered a RAG pipeline over 12,500+ PubMed documents, reducing information retrieval time by 40%.
Deployed 3 Streamlit applications and managed 20+ MLflow experiments, improving model reproducibility and tracking efficiency.
Collaborated within Agile teams to deliver ML solutions aligned with stakeholder requirements.