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AI Engineer with 2+ years in GenAI and React.js
AI is analyzing your overall score…
Identifying your key strengths…
Evaluating your skill match against the job requirements…
Assessing your cultural and operational fit
M.Tech CSE student at IIITNR with hands-on experience in AI/ML, full-stack development, predictive analytics, REST API development, and scalable application design. Skilled in Python, Java, React.js, FastAPI, and data-driven problem-solving with exposure to SDLC, testing, debugging, documentation, and process improvement.
IIITNR
Mtech · CSE – Data Science and Artificial Intelligence
August 1, 2024 – Present
SSIPMT, Raipur
Btech · CSE
August 1, 2017 – June 1, 2021
Self-Employed
Front-End Developer | UI/UX Developer
January 1, 2023 – December 31, 2024
India
Intelligent Power Demand Forecasting - AI + Full Stack + Deployment
June 18, 2026 – Present
Developed a scalable, end-to-end electricity demand forecasting system for Apex Power Utilities using real-world noisy data and external APIs. Built predictive modeling workflows integrating weather and localized holiday data; conducted data analysis, data cleaning, and feature engineering to improve forecast accuracy. Developed backend microservices using Python and FastAPI for RESTful API development; built interactive frontend dashboards using React.js and Chart.js to visualize load forecasts, weather, and holiday trends. Followed SDLC-oriented development with unit-level validation, debugging, and comprehensive documentation; containerized the full application using Docker for deployment readiness.
Indian Legal Assistant – RAG-based Legal Advisor (GenAI)
June 18, 2026 – Present
Built a scalable legal-assistance application using Retrieval-Augmented Generation (RAG) and backend services to provide contextual responses from the Indian Constitution and Supreme Court verdicts. - Developed a scalable AI pipeline integrating ChromaDB for vector storage, MiniLM for semantic embeddings, and GPT-40-mini with LangChain for retrieval, generation, and API integration workflows. - Implemented metadata filtering, document weighting, and intelligent chunking to improve data processing, factual accuracy, and retrieval precision. - Evaluated the system using RAGAS, achieving 87.3% factual accuracy and 92.1% retrieval precision; performed testing and debugging, and built a Streamlit interface for real-time query processing with legal citations and source attribution. - Research paper derived from this project has been accepted by HNLU for the next stage of evaluation and publication in their edited volume (certificate awaited).
Live vs. Spoofed Voice Classification | Machine Learning Project
June 18, 2026 – Present
Built a high-accuracy binary audio-classification system for detecting spoofed voices, achieving 92.64% validation accuracy using LightGBM and 90.30% using a ResNet-based deep learning model. Utilized deep learning techniques and feature engineering to extract key audio characteristics and improve detection accuracy. Implemented models using Python, TensorFlow/PyTorch, and signal processing techniques, optimizing classification performance on real and synthetic voice datasets.
Shopistic - Redefining E-commerce | MERN Stack Project
June 18, 2026 – Present
Developed a full-stack e-commerce application using React.js for the frontend and Node.js with Express.js for the backend; implemented secure authentication with JWT (refresh and access tokens) and CRUD operations for products. Integrated Stripe for payment processing and designed analytics functionality; utilized MongoDB for data storage, Axios interceptors for token handling, and deployed the application successfully.
Online Computer Programming Lesson
Effcon Technologies
June 18, 2026 – Present
Machine Learning for Engineering and Science Applications (Score: 76/100)
NPTEL
June 18, 2026 – Present
C Programming Language
IIT Kharagpur
June 18, 2026 – Present
React.js
Effcon Technologies
June 18, 2026 – Present
Cultural Fit Analysis
Based on the psychometric test score of 0/500, there is no positive indication of cultural fit. Further assessment is required.
Soft Skills & Operational Fit
Based on the provided assessment scores (English: 0/100, Psychometric: 0/500), there is no evidence of strong soft skills or operational fit. Further assessment is required.