My Experience
Acmegrade Pvt Ltd
Cloud Computing Intern
Engineered three production-grade conversational AI bots using AWS Lex — implementing intent recognition, slot filling, multi-turn dialogue management, and automated customer-service workflows.
Developed a "Car Buying Assistant" backend integrating API-driven logic to dynamically query and filter 20+ car models by price, colour, and delivery preferences using CRUD operations and JSON data exchange.
Designed conversation flows for an Online Shopping bot and a Railway Ticket Booking system (replicating IRCTC General/Tatkal quota logic) with async/await request handling and scalable intent routing.
Conducted functional and integration testing with Postman to validate REST API endpoints, optimising backend response pipelines in production-simulated cloud environments.
Education
B.Tech — Computer Science & Engineering
Sandip University, Nashik
Relevant Coursework: Data Structures & Algorithms, Cloud Computing, Operating Systems, Distributed Systems, Database Management Systems, Object-Oriented Programming.
Thesis: Innovations in Sustainable Engineering Practices.
My Resume
Education
B.Tech — Computer Science & Engineering
Sandip University, Nashik (Sep 2022 – Sep 2026)Coursework: DSA, Cloud Computing, OS, Distributed Systems, DBMS, OOP. Thesis on Innovations in Sustainable Engineering Practices.
10+2 (CBSE)
OM Public School (2008 – 2022)Completed secondary and senior secondary education under CBSE curriculum.
Certifications
Artificial Intelligence & Machine Learning
Learn Flu (AICTE Approved)Entrepreneurship Essentials
NPTEL, IIT Kharagpur — Score: 50%Backend Technologies
Cloud & DevOps
Databases
AI / Machine Learning
Tools & Frontend
Work Experience
Cloud Computing Intern
Acmegrade Pvt Ltd (Dec 2024 – Jan 2025)Built three production-grade AWS Lex conversational AI bots with intent recognition, slot filling, and multi-turn dialogue. Developed a Car Buying Assistant API filtering 20+ models; designed flows for an Online Shopping bot and IRCTC-style Railway Booking system. Validated REST endpoints via Postman and optimised backend pipelines in cloud-simulated environments.
Projects
Spacifyer — NASA Space Apps Challenge
Full-Stack Web App · Oct 2024Full-stack, cloud-hosted app consuming NASA's space-weather REST APIs to visualise real-time geomagnetic data. Modular backend architecture with clean separation of concerns. Deployed on Vercel with automated CI/CD from GitHub for zero-downtime releases. Awarded 'Galactic Problem Solver' by NASA International Space Apps Challenge 2024.
Titanic Survival Prediction
Machine Learning · Aug – Oct 2025End-to-end ML pipeline in Python (Pandas, Scikit-learn) with full ETL: missing-value handling, feature engineering (Title extraction, FamilySize), and train/test splitting. Benchmarked Logistic Regression, Random Forest, and XGBoost; applied Randomised SearchCV hyperparameter tuning for optimal accuracy.
