Serial Entrepreneur & Technical Leader with proven expertise in Large Language Models, Distributed Systems, and Blockchain Architecture. Currently scaling AI solutions at Reclevo Infotech while pioneering carbon credit tokenization at Xphora AI.

📊 Impact Metrics: 60% GPU optimization • 98% system accuracy • 40% cost reduction • $1M+ funding secured

Current Roles:
  - Co-Founder & CTO: "Reclevo Infotech (JV Xphora X Inovativa)"
  - Founder & CEO: "Xphora AI Technology"
  
Team Leadership:
  - Cross-functional teams: "3+ engineering teams"
  - Model training: "100+ ML models in production"
  - Concurrent systems: "50+ requests with <100ms latency"
  
Business Impact:
  - Revenue optimization: "65% margin improvement"
  - Cost reduction: "CAC from $200 → $50"
  - User engagement: "+40% through AI automation"

• LLM Fine-tuning: PEFT optimization on Qwen-3B using Amazon SageMaker (60% memory reduction)
• MLflow Orchestration: Experiment tracking across 100+ models with cross-team collaboration
• Real-time AI: 95% accuracy sign language recognition + emotion detection for accessibility
• Production ML: Microservices handling 50+ concurrent video generation requests

• Smart Contract Development: Celo blockchain integration for carbon credit tokenization
• DeFi Architecture: Transparent environmental impact tracking with immutable records
• Tokenomics Design: Sustainable reward mechanisms for carbon offset verification

• Microservices: Node.js/Express with WebSocket scaling to 100+ concurrent streams
• Database Architecture: PostgreSQL + Prisma with real-time sync capabilities
• Cloud Infrastructure: AWS SageMaker + multi-region deployment strategies

Languages:        Python • TypeScript • Solidity • SQL
ML Frameworks:    PyTorch • TensorFlow • Hugging Face Transformers
LLM Tools:        LangChain • Llama Index • Amazon SageMaker • MLflow
Fine-tuning:      PEFT • LoRA • QLoRA • RLHF
Vector DBs:       Pinecone • Weaviate • ChromaDB

Smart Contracts:  Solidity • Celo • Ethereum
Web3 Tools:       Web3.js • Ethers.js • Hardhat
DeFi Protocols:   Carbon Credit Tokenization • Environmental Impact Tracking
Consensus:        Proof of Stake • Layer 2 Solutions

Backend:          Node.js • Express.js • NestJS • FastAPI
Databases:        PostgreSQL • MongoDB • Redis • Snowflake
Cloud:            AWS • Google Cloud • Vercel
DevOps:           Docker • Kubernetes • CI/CD • Monitoring
Real-time:        WebSockets • Socket.io • Server-Sent Events

^{Scale: 1000+ daily users • Tech: SageMaker, MLflow, Microservices}

// Key Innovations
- PEFT Fine-tuning: Qwen-3B optimization (60% memory reduction)
- MLflow Pipeline: 100+ model experiment tracking
- Video Generation: 50+ concurrent requests, 98% viseme accuracy
- Smart Scraping: 1000+ notifications/day, 99% accuracy

Business Impact: Reduced training costs by 60%, increased engagement by 40%

^{Funding: $1M secured • Tech: Celo, Smart Contracts, AI Verification}

// Smart Contract Architecture
contract CarbonCredit {
    mapping(address => uint256) public carbonBalance;
    
    function verifyAndMint(bytes32 _activityHash, uint256 _credits) 
        external onlyVerifier {
        // AI-powered verification logic
        carbonBalance[msg.sender] += _credits;
        emit CreditMinted(msg.sender, _credits, _activityHash);
    }
}

Technical Achievement: 40% reduction in manual validation, transparent tracking

^{Scale: 50+ stations • Tech: PowerBI, Airtable, Real-time Sync}

# Performance Optimization
def optimize_resource_allocation(station_data):
    """
    Real-time resource optimization algorithm
    Processes 1000+ daily updates with 5-minute decision cycles
    """
    return optimized_allocation  # 60% time reduction, 40% response improvement

^{Recognition: Top 10 Google India • Tech: 3D Environment, Real-time ML}

• Computer Vision: 95% accuracy sign language recognition
• Emotion AI: Autism support through facial expression analysis
• Real-time Rendering: <100ms latency for 100+ concurrent users

Education:
  - "B.Tech Mechanical Engineering (GGV) - CGPA: 8.8/10"
  - "Bachelor's Data Science (IIT Madras) - CGPA: 7.1/10"

Certifications:
  - "Microsoft PL-300 (Power BI)"
  - "SnowPro Core Certification"
  
Continuous Learning:
  - "Advanced Deep Learning Specialization"
  - "Blockchain Development Bootcamp"
  - "AWS Solutions Architect Track"

# Notable Contributions
├── 🤖 ml-optimization-toolkit/     # PEFT fine-tuning utilities
├── ⛓️  carbon-credit-contracts/    # Smart contract templates  
├── 📊 realtime-analytics-engine/   # High-performance data processing
└── 🎓 edu-accessibility-ai/        # Inclusive learning tools

"Building production-grade AI systems that scale to millions while solving real-world problems through blockchain transparency and sustainable innovation."

Core Principles:

• 🚀 Performance-First: Every optimization counts at scale
• 🔒 Security-Native: Blockchain-level trust in all systems
• 🌍 Impact-Driven: Technology for positive environmental and social change
• 📊 Data-Informed: Metrics-driven decision making