AI/ML Engineer building practical machine learning systems.
BS Artificial Intelligence student at FAST-NUCES focused on computer vision, LLM applications, RAG, and production-oriented AI engineering.
About
I am a final-year BS Artificial Intelligence student at FAST-NUCES with a strong focus on practical, deployable AI engineering. I like building systems where the model is only one part of the solution.
My work spans across computer vision, LLM applications, retrieval systems, and backend API architecture. Rather than relying on boilerplate generation, I engineer end-to-end solutions—from data collection and model fine-tuning to building the necessary infrastructure for production deployment.
Featured Work
Detailed case studies of my primary engineering projects.
OmniDrive AI
Intelligent Automotive Diagnostic Ecosystem
An automotive diagnostic platform combining computer vision, sensor data, OBD-II telemetry, and retrieval-augmented assistance.
Architecture
Core Modules
Diagnostic Engine
- -Real-time OBD-II sensor data ingestion and preprocessing pipeline.
- -Computer vision classification using a custom YOLO11-Large model.
- -GPS/IMU sensor fusion stabilized with a 1-D Kalman filter.
- -FastAPI inference server connecting the mobile client to the ML models.
Retrieval Assistance
- -RAG-based DIY car assistance module.
- -Semantic search across technical automotive documents using pgvector.
- -Context-aware generation for mechanical troubleshooting.
Platform Infrastructure
- -Supabase PostgreSQL handling auth, roles, and relational storage.
- -Role-based marketplace supporting customers, vendors, riders, and admins.
- -Flutter mobile application for cross-platform delivery.
AI Job Application Agent
An agentic workflow for discovering, evaluating, and assisting with job applications.
Architecture
Key Implementation
- •Job scraping and extraction using browser automation (Playwright).
- •LLM reasoning applied to eligibility analysis and CV parsing.
- •Structured workflows with human-in-the-loop review steps.
- •Automated logging and tracking via Google Sheets integration.
MaintainIQ
A hybrid retrieval pipeline combining dense and lexical search to improve technical diagnostic retrieval.
Key Implementation
- •Semantic and lexical retrieval mechanisms (FAISS + BM25).
- •Reciprocal Rank Fusion (RRF) for optimal document ranking.
- •FastAPI backend for high-throughput search queries.
- •Technical documentation processing and chunking strategy.
Other Systems & Experiments
Serene
AI wellness companion with LoRA fine-tuning and local emotion detection.
NewsLens
Fine-tuned BERT classifier for real-time news headline categorization.
TicketIQ
Zero-shot and few-shot LLM classification for support tickets.
Hybrid Travel Recommendation
LLM-based recommendation system using FAISS and Annoy semantic retrieval.
Experience
AI/ML Engineering Intern
- -Designed and deployed applied AI systems focusing on LLMs, RAG pipelines, and NLP classification.
- -Engineered modular applications integrating Hugging Face models, FAISS vector stores, and Streamlit interfaces.
- -Implemented fine-tuning pipelines using LoRA for custom instruction-following tasks.
AI Developer Intern
- -Built full-stack applications using React, Next.js, and Supabase.
- -Integrated the Gemini API and automated LLM workflows using n8n orchestration.
- -Developed data pipelines for web scraping, translation, and structured data generation.
Teaching Assistant — Programming Fundamentals
- -Mentored students in C++ and core programming fundamentals.
- -Evaluated code quality, logic-building, and project implementation.
Technical Toolkit
AI / ML
- Python
- PyTorch
- Scikit-learn
- Computer Vision
- NLP
- LLMs
- RAG
- LoRA
Models & Retrieval
- YOLOv11
- BERT
- GPT-Neo
- DistilRoBERTa
- BART-large-MNLI
- FAISS
- BM25
- SentenceTransformers
Backend & Data
- FastAPI
- REST APIs
- PostgreSQL
- Supabase
- Firebase
- Node.js
Frontend
- Flutter
- React
- Next.js
- Streamlit
Infrastructure & Tools
- Docker
- Git
- GitHub Actions
- Vercel
- n8n
- Postman
Certifications
AI/ML Engineering Internship Certificate
6-week AI/ML Engineering internship.
AI Developer Internship Certificate
Full-stack AI application development using React, Next.js, and Gemini API.
Have an AI problem worth building?
I am currently open to full-time AI/ML Engineering roles. If you're looking for an engineer who focuses on deployable, production-ready systems rather than just notebooks, let's talk.