AI Developer experienced in building scalable, modular systems and end-to-end AI pipelines. Skilled in applying LLMs, NLP, RAG, and Generative AI to production-focused projects. Developed AI systems using vector search, REST/WebSocket APIs, and containerized cloud deployment with an emphasis on reliable architecture and efficient workflows.
What I Do:
- Advanced RAG Systems — hybrid retrieval, vector search, knowledge graphs
- LLM Engineering — prompt orchestration, fine-tuning, multi-agent workflows
- API Development — REST, WebSocket, GraphQL using FastAPI with production grade design
- Production ML — Dockerized services, CI/CD pipelines, cloud deployments
- Multimodal AI — Computer Vision (YOLO, OpenCV), NLP, OCR pipelines
How I Work:
- Lead and collaborate with teams to architect scalable solutions
- Design robust APIs that handle real-time communication and high-traffic workflows
- Communicate complex technical concepts to diverse audiences
- Bridge the gap between research and production deployment
MindCanvas — AI Knowledge Graph System
🏆 Winner at Hackprix Hackathon S2
Transform browsing data into an intelligent, queryable knowledge graph. AI-powered system that analyzes web content, extracts relationships, and creates interactive visualizations for semantic exploration and learning progress tracking.
- Built full-stack application with FastAPI backend and React frontend
- Developed Chrome extension for seamless one-click data export and processing
- Implemented RAG-powered chatbot for natural language queries about your knowledge
- Designed interactive graph visualizations with Cytoscape.js featuring multiple layout algorithms
- Impact: 3x faster retrieval, 75% improvement in identifying latent relationships across knowledge domains
Supabase LangChain Cytoscape.js FastAPI React OpenAI Groq pgvector
Predictive Maintenance — Production MLOps Pipeline
End-to-end ML system predicting equipment failures using ensemble learning and industrial sensor data.
- Built automated CI/CD pipeline (GitHub Actions, Docker, AWS ECS/ECR)
- Implemented MLflow for experiment tracking, model versioning, and automated retraining
- Engineered data pipeline using SMOTE for improved class balance
- Impact: 91.2% accuracy, deployment time reduced from hours to minutes
MLflow FastAPI Docker AWS ECS/ECR Scikit-learn GitHub Actions
Enhanced AI-powered interview platform with resume parsing, cheat detection, and LLM-driven assessments.
- Built cheat detection module using YOLOv11, OpenCV, and voice analytics
- Integrated STT/TTS and voice cloning with 90% transcription accuracy
- Developed multi-agent AI assistants with persistent memory (LangChain, CrewAI)
- Deployed LLM-based virtual assistant for real-time, context-aware answers
- Optimized API latency using request batching and caching strategies
- Impact: 30% reduction in hiring cycles, 1000+ daily assessments processed
LangChain OpenAI YOLOv11 Docker AWS EC2 Nginx
| 🔍 AI/ML & LLMs | ⚙️ MLOps & API Development |
|---|---|
| RAG Systems • Vector Search | FastAPI • REST • WebSocket • GraphQL |
| LangChain • Multi-Agent Systems | Docker • MLflow • CI/CD |
| Prompt Engineering • Fine-tuning | AWS (EC2, ECS, ECR) • Model Monitoring |
| Transformers • Embedding Optimization | Nginx • GitHub Actions |
| 🎛️ Computer Vision & NLP | 📊 Data & Databases |
|---|---|
| YOLO • OpenCV • Object Detection | Pandas • NumPy • PySpark |
| OCR Pipelines • TensorFlow | PostgreSQL • MongoDB • Supabase |
| Sequence Models • Scikit-learn | ChromaDB • Qdrant • Redis |
Languages & Tools: Python • SQL • JavaScript • Git • Shell Scripting
API & Backend: FastAPI • REST APIs • WebSocket • GraphQL • Postman • Nginx
Soft Skills: Technical Communication • Team Leadership • Mentoring • Project Coordination • Pitching Ideas
- Top Performer Recognition — Delivered production-grade AI features serving 1000+ daily users
- 7+ Hackathons — Multiple podium finishes in GenAI and MLOps competitions
- 6+ Technical Articles — Published on AI/ML topics on Medium
- Research Publication — Co-authored paper on Graph-Augmented RAG systems
- 900+ GitHub Commits — Across 50+ AI/ML projects
- 200+ LeetCode Problems — Consistent problem-solving practice
- Vector optimization & multi-hop retrieval architectures
- Advanced MLOps patterns (Kubernetes, distributed training)
- Graph-augmented reasoning systems
- Implementing cutting-edge AI research in production
I'm open to collaborating on:
- LLM-driven knowledge systems & RAG architectures
- Graph-based reasoning & multi-agent systems
- Production ML pipelines & MLOps infrastructure
- Intelligent retrieval & data processing systems
Open to full-time opportunities and freelance projects in AI/ML and Backend Engineering.
📫 Reach out: huzaif027@gmail.com | LinkedIn | Portfolio