Profile
Full-stack developer and data practitioner with hands-on experience in AI/ML, data analysis, and production engineering — shaped through multiple industry internships and real-world projects.
Experience
Machine Learning Intern
Centre for Railway Information Systems (CRIS)
May 2025 - Jun 2025
- Processed 450K+ freight records and engineered 20+ domain-specific features for ML-based time prediction pipelines on real Indian Railways operational data.
- Boosted model accuracy by 27% using LightGBM with hyperparameter tuning; benchmarked 5+ algorithms (Random Forest, XGBoost, SVR) achieving R²: 0.78 (loading) and R²: 0.72 (unloading).
Data Analyst Intern
TRINITI
Jul 2024 - Jul 2024
- Completed coursework in Data Analytics, Statistics, and visualization tools (Excel, MySQL, Tableau, Python) — applying statistical methods to analyze, clean, and transform complex datasets, delivering actionable insights through reports and dashboards to support business decision-making.
Software Development Intern
General Software & Consultancy Services (GSCS)
May 2024 - Jul 2024
- Managed the AppKube cloud monitoring project overseeing 10+ AWS EC2 instances; reduced system monitoring time by 30% through automated dashboards and real-time alert pipelines.
- Delivered EC2 reporting solutions serving 5+ enterprise client environments, improving operational observability and incident response efficiency across production infrastructure.
Projects
Creatorjoy RAG — YouTube Content Intelligence
render.comBuilt a full-stack RAG platform where creators paste two YouTube URLs and ask why one outperformed the other — powered by a LangGraph StateGraph with 4-class query routing, fastembed ONNX BGE-small embeddings on pgvector HNSW, 3-stage transcript cascade (youtube-transcript-api → Supadata.ai → Groq Whisper V3), and SSE streaming with inline timestamp citations.
DiagnoseAI — Codebase & Meeting Intelligence SaaS
diagnose-ai.vercel.appBuilt and deployed a full-stack SaaS platform enabling developers to index any GitHub repository and query codebases via natural language — powered by a LangChain + RAG pipeline with pgvector (384-dim HuggingFace BGE embeddings) and Groq Llama 3.1 for context-aware answers with file-level references.
Multi-AI Hedge Fund Simulator
Built a multi-agent trading simulator encoding strategies from 15+ legendary investors into role-based agents (fundamentals, sentiment, risk arbitrage) with an agentic orchestration layer for signal-sharing and unified portfolio decision-making.
Achievements
IBM DevOps, Agile & Design Thinking (IBMCE) · IBM
Introduction to AI · Infosys Springboard
OfficeMaster On PowerBI (BE 10X) · OfficeMaster