Software Engineer specializing in AI/ML, Mobile Development, and Cloud Infrastructure
Currently building intelligent nutrition solutions at NutriScan - serving 20K+ active users with contextual AI chatbots and multimodal meal analysis systems.
- 💼 Software Engineer at NutriScan (June 2024 - Present)
- 🎓 Computer Engineering Graduate from Xavier Institute of Engineering (2024)
- 🤖 AI/ML Specialist - Built RAG chatbots handling 100+ daily questions with 90%+ accuracy
- ☁️ DevOps Engineer - Managing 99.8% uptime across Azure and GCP infrastructure
- 📱 Mobile Developer - Full-stack Flutter development for iOS, Android, and Web platforms
- ✍️ Technical Writer - Published AI/ML implementation guides on Medium
AI/ML: Fine-tuning, RAG, Unsloth, LlamaIndex, Computer Vision, NLP, Entity Recognition
Cloud & Backend: Azure, Google Cloud Platform, CI/CD, PostgreSQL, Supabase, Firebase, RESTful APIs
Languages & Frameworks: Python, Dart, C#, SQL, C++, Flutter, Unity
Development Tools: Git, Docker, WebSocket, JWT Authentication, Provider State Management
Fine-tuned Qwen2.5-VL model achieving 89.3% accuracy for product identification and counting
ML system predicting 6 health conditions with 0.853 average AUC score using NHANES data (33K+ records)
AI-powered billing app with 91% extraction accuracy using Gemini Vision API and entity recognition
- Vision-Language Model Fine-tuning - Complete guide to Qwen2.5-VL fine-tuning
- Personalized Chatbots with LlamaIndex - RAG implementation tutorial
- Flutter In-App Purchases - Complete implementation guide
🔥 Current Role: Leading full-stack development of nutrition AI platform with dual VLM/LLM architecture for meal recognition and nutrient evaluation
⚡ Key Achievements:
- Built contextual RAG system processing 100+ daily questions
- Architected dual model system with VLM + LLM evaluation
- Managed DevOps operations with 99.8% uptime
- Delivered 40% performance improvement through optimizations
"Building intelligent systems that bridge AI capabilities with real-world applications"