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/