I am a forward-thinking Software Engineer and AI/ML Specialist with a product engineering mindset. Currently pursuing a B.E. in Computer Science & Engineering at Sona College of Technology, I specialize in building highly scalable, reliable full-stack applications and integrating machine learning workflows to solve real-world problems.
- Software Engineering: Architectural design patterns, Node clustering, concurrency handling, and relational/non-relational database schemas.
- AI/ML & Deep Learning: Natural Language Processing, Predictive Analytics, Geospatial Clustering, and Prompt Engineering.
- Full Stack Development: End-to-end SDLC ownership, building responsive user interfaces, role-based security, and performance-optimized database structures.
- Product Mindset: Translating complex system requirements into seamless user-facing features, with an emphasis on performance and clean, maintainable systems.
Open To:
- Software Engineering & Full-Stack Development roles
- AI / ML Engineering opportunities
- Open Source and enterprise-scale contributions
| Domain | Proficiency | Details |
|---|---|---|
| Machine Learning & Deep Learning | Advanced | Classification, regression, ensemble models (LightGBM, XGBoost, CatBoost), cross-validation, and Scikit-Learn pipelines. |
| Natural Language Processing | Intermediate | Integrating LLMs (Google Gemini), parsing unstructured textual queries into structured schemas, and Prompt Engineering. |
| Geospatial Analytics & Clustering | Intermediate | Density-based spatial clustering (DBSCAN), GIS data preprocessing, Folium visualization, and urban planning analytics. |
| Generative AI | Advanced | AI-assisted medical triage bots, intelligent booking assistants, automated workflows, and Generative AI for Data Science. |
June 2026 – Present (Remote)
- Built and deployed an enterprise-level e-commerce dashboard using React, Node.js, Express, and MongoDB.
- Implemented a high-performance backend using Node clustering, enhancing multi-core execution efficiency.
- Configured Mongoose data modeling and race-condition-safe product seeding to prevent double-transactions under high loads.
- Designed responsive client interfaces featuring complex seller panels, checkout pipelines, and JWT session handling.
React.js Node.js Express.js MongoDB JWT Node Clustering Mongoose
2026 (Remote)
- Selected nationwide for a selective virtual cohort focused on practical applications of artificial intelligence.
- Trained, evaluated, and deployed machine learning classifiers on complex industry datasets.
- Collaborated on research documentation assessing model accuracy, precision, and recall metrics.
Python Scikit-Learn Machine Learning Predictive Analytics Data Science
| Recognition | Details |
|---|---|
| Nasscom Hackathon Finalist | Recognized in the Top Team out of 5,743 nationwide entries for the AI-assisted Telemedicine platform. |
| Flipkart Hackathon Top Team | Ranked among the top teams out of 30,000+ entries for Gridlock traffic demand forecasting. |
| Srinivasan Ramanujan Mathematics Competition | Achieved excellent ranking in the National Mathematics Competition (2024). |
| Samitha Hackathon Recognition | Acknowledged for outstanding project architecture and AI-chatbot integration. |
| Deloitte Tech Job Simulation | Completed advanced software engineering and technical consulting simulations. |
## 🏆 GitHub Trophies
## 📈 Contribution Activity
learning: "System Design, Microservices, and Advanced Deep Learning Architectures"
building: "Sanguis AI (Blood Donation Intelligence Platform) & Nabula E-Commerce"
exploring: "RAG Systems, Vector Databases (Pinecone/Milvus), and LLM Agents"
open_to: "Full Stack Developer Roles & AI/ML Engineer Internships/Contracts"