Machine Learning Engineer specializing in LLM-based systems, RAG architectures, and production AI deployment.

Recent MS graduate with hands-on experience building production-grade ML systems for industry partners.

• 🤖 LLM Systems & RAG Architectures - Document intelligence, semantic search, context-grounded generation
• ⚡ Production ML Deployment - FastAPI, Docker, cloud services with <2s latency
• 🛡️ Reliable AI Systems - Output validation, hallucination detection, evaluation frameworks
• 💻 Full-Stack ML - End-to-end systems from data pipelines to user interfaces

• ✅ 3 industry partner projects delivered to production
• ✅ 82-85% accuracy on real-world validation
• ✅ <2s latency optimization across systems
• ✅ 40% hallucination reduction through systematic engineering
• ✅ Google Cloud Certified in ML and GenAI

📜 View All Certifications: Credly Profile

Software Developer

• Built Python backend systems and ETL pipelines processing 50K+ daily records for 20+ client accounts
• Designed data ingestion workflows reducing processing time by 60% through optimization
• Developed and deployed 3 major production features serving 100+ users with 99.5% uptime
• Automated 5 critical workflows eliminating 15+ hours/week of manual work
• Collaborated with cross-functional teams (design, product, clients) in fast-paced environment

Software Developer Intern

• Contributed to backend development for large-scale government data applications
• Built data validation workflows and REST API integrations
• Collaborated with teams to deliver production-ready components in regulated environment

Chrome Extension | AI-Powered | Privacy-First

Intelligent Chrome extension acting as a personal learning companion with real-time AI insights.

Key Features:

• 🤖 AI-powered content analysis and insights
• 📝 Smart note-taking with auto-summarization
• 🎯 Focus timer with Pomodoro technique
• 📊 Learning progress tracking
• 🔖 Intelligent bookmarking system

Tech Stack: JavaScript · Chrome APIs · AI Integration

CLI Tool | TypeScript | Semantic Analysis

ML-driven code intelligence system that automatically analyzes JavaScript/TypeScript repositories.

Key Achievements:

• 📊 Automatic framework detection (React, Next.js, Vue, Express, +11 more)
• 🤖 Semantic code search with LLM-powered reasoning
• 🔧 Modular plugin architecture for extensibility
• 🎯 35% reduction in false positives through validation guardrails

Tech Stack: TypeScript · Node.js · OpenAI API · AST Parsing · Vector Search

Full-Stack RAG | <800ms Latency | Production-Grade

Route-aware visa assistant providing context-grounded recommendations with verified requirements.

Key Achievements:

• 🎯 Complete RAG pipeline: Document ingestion → chunking → embedding → retrieval → generation
• ⚡ 73% latency improvement: Optimized from 3s to <800ms with Redis caching
• 🛡️ Context-grounded responses with automatic citation tracking
• 📊 85%+ answer quality maintained at scale through systematic evaluation

Tech Stack: FastAPI · React · PostgreSQL · Redis · ChromaDB · Gemini AI · Docker

Specialized ML Skills:

• 🧠 LLMs: OpenAI GPT-4 · Google Gemini · Anthropic Claude | Prompt Engineering · Fine-tuning · Inference Optimization
• 🔍 RAG Systems: Vector DBs (Pinecone, ChromaDB, FAISS) | Semantic Search | Hybrid Retrieval | Document Processing
• 🛡️ ML Reliability: Output Validation · Hallucination Detection · Evaluation Frameworks · Error Handling
• 📊 ML Engineering: Feature Engineering · Model Deployment · A/B Testing · Performance Monitoring