---
title: "Muhammed Ajzel - AI Engineer Intern in Bengaluru | Tal"
description: "Meet Muhammed Ajzel, AI Engineer | GenAI · LangChain · RAG · MCP | Data Scientist · Analytics · Forecasting | Oracle OCI GenAI Certified based in Bengaluru. AI stack includes claude, hugging face, and langchain. Explore public work links including github and mohammed-ajzel.lovable.app."
image: "https://tal.club/meet/mohammed-ajzel/share-image"
---

# Muhammed Ajzel on Tal

## Headline

AI Engineer \| GenAI · LangChain · RAG · MCP \| Data Scientist · Analytics · Forecasting \| Oracle OCI GenAI Certified

## About

I build AI systems that actually work in production — not just in Jupyter notebooks\. With an M\.Sc\. in AI, ML & Data Science \(Yenepoya University, 2025\) and Oracle Certification in Generative AI, I specialize in turning cutting\-edge research into deployable solutions: LLM\-powered pipelines, agentic workflows, real\-time ML APIs, and computer vision systems\. 🔹 My most recent project? As an AI Automation Extern at Wayfair × Extern, I engineered a fully autonomous market intelligence agent — a 30\+ node multi\-LLM orchestration \(Mistral \+ Gemini\) that replaced manual research with a zero\-touch pipeline\. It scraped Amazon, Instagram & Pinterest, synthesized trend signals, generated AI visual moodboards, and auto\-published HTML reports to Google Drive\. No human in the loop\. End to end\. 🔹 At IBM, I deployed a Flask\-based ML model \(Random Forest\) achieving 92% R² accuracy on 1,000\+ data points for energy consumption prediction — with real\-time APIs handling 100\+ predictions/sec and a dashboard that cut manual analysis time by 40%\. 🔹 Earlier, as a Data Analyst at Domino's, I built demand forecasting models that reduced stock\-outs by 98% during peak hours and cut ingredient waste by 20% — proof that ML doesn't have to be flashy to be valuable\. What I bring beyond the technical: → Full\-stack ML mindset: from data wrangling to deployment to monitoring → Comfort with ambiguity — I've built pipelines with no playbook → Production\-first thinking: uptime, scalability, and real business metrics matter to me \. Tech stack: Python · LangChain · LangGraph · MCP · RAG/FAISS · Fast API · Docker · LLM Fine\-tuning \(QLoRA\) · Mistral · Gemini · Groq · Claude API · n8n · PyTorch · Hugging Face\. Currently open to: AI/ML Engineer · Generative AI Engineer · AI Automation · Data Scientist roles Open to any location in India \| Remote Worldwide Let's connect: Ajuajzel10@gmail\.com \| www\.vitaely\.me/ajzel

## Location

Bengaluru

## AI stack

claude

hugging face

langchain

langgraph

mcp

n8n

## Work experience

AI Engineer Intern at Infosys Springboard, Feb 2026 \- Apr 2026 · 2 mo, Remote, Built an enterprise\-grade AI email categorization and prioritization system using NLP, transformer\-based models, and prompt engineering\. Delivered a production\-ready solution for automated classification and priority ranking\.

AI Automation Extern at Extern, Jan 2026 \- Mar 2026 · 3 mos, Remote, Wayfair × Extern Engineered a production\-grade autonomous AI agent for market intelligence — replacing manual research with a zero\-touch pipeline that ingests, reasons, and reports\. • Architected a multi\-source scraping system across Amazon, Instagram, Pinterest & industry blogs — processing real\-time trend signals at scale • Built a 30\+ node multi\-LLM orchestration \(Mistral \+ Gemini\) handling data cleaning, deduplication, category validation, and micro\-segment synthesis • Engineered a fully autonomous market intelligence agent that eliminated manual trend research — a zero\-touch pipeline from ingestion to published HTML report, with no human intervention required\. • Delivered actionable market intelligence: $62\.9B TAM, 9\.59% CAGR, \+180% YoY search growth signal — with SKU expansion recommendations Stack: n8n · Mistral AI · Google Gemini · Hugging Face · Agentic Workflows · Prompt Engineering · Google Drive API

Machine Learning Intern at Cognifyz Technologies, Dec 2025 \- Jan 2026 · 2 mos, Greater Bengaluru Area, Built and deployed multiple ML web apps during Cognifyz internship using Python \+ Flask\. Developed a Restaurant Recommender System, Cuisine Classification model, and Restaurant Rating Prediction app\. Worked on end\-to\-end ML pipeline: data preprocessing, feature engineering, model training, evaluation, and deployment\.

AI Intern at IBM, Mar 2025 \- Jul 2025 · 4 mo, Bangalore Urban, Karnataka, India, • Built and deployed a Flask\-based ML model \(Random Forest\) achieving 92% R2 accuracy on 1,000\+ data points for energy consumption prediction\. • Developed real\-time APIs and a dashboard with Chart\.js, enabling 100\+ predictions/sec and reducing manual analysis time by 40%\. • Automated model retraining with user\-uploaded datasets, improving forecast adaptability by 30%\. • Ensured solution scalability with SQLite\-backed storage and 95%\+ uptime during testing\.

## Education

Master of Science \- MS, Computer Science, Yenepoya University

Bachelor's degree, Computer Application, Jamia hamdard

## Public links

- github: https://github\.com/Ajzel
- mohammed\-ajzel\.lovable\.app: https://mohammed\-ajzel\.lovable\.app/

[View the original profile](https://tal.club/meet/mohammed-ajzel)

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