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Ayush Mondal

@ayushmondal

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Entry-level AI/ML and data science intern building deployable churn models and RAG assistants.

India

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What I'm looking for

I’m looking for an entry-level role where I can build deployable ML and data pipelines, and ship AI features (RAG/LLMs) with clean APIs. I want hands-on projects using Python, AWS, and modern frameworks, plus learning through mentorship.

I’m an electronics and communication engineering student who leans into AI/ML, data engineering, and backend development. I enjoy turning messy data and documents into systems that can train, search, and serve useful outputs reliably.

During my internships, I built an end-to-end Customer Churn Prediction model using Python and Scikit-learn, reaching 87 accuracy, and prepared the trained model for deployment using Joblib. I also developed a Hospital Management System backend with Node.js, Express.js, and MongoDB—implementing REST APIs and Mongoose schemas for core workflows using MVC architecture, async/await, and centralized error handling.

I’ve also worked on serverless data workflows, developing a Python-based AWS Glue + AWS Lambda ETL pipeline to ingest, clean, and transform raw CSVs into analytics-ready outputs. In parallel, I created an AWS data pipeline project using multiple services to improve automation and data quality while reducing manual preprocessing effort.

My recent focus includes building RAG-powered applications that support natural-language CV querying, using LangChain, FAISS, and MistralAI. I’m excited by practical, deployable work across model development, data pipelines, and API-backed experiences that follow established technical standards.

Experience

Work history, roles, and key accomplishments

Allotrope Systems Intern

Allotrope Systems Private Limited

Developed a Hospital Management System backend using Node.js, Express.js, and MongoDB, implementing REST APIs and Mongoose schemas for core workflows and applying MVC architecture with async/await and centralized error handling.

Node MongoDB REST APIs Mongoose MVC Async Await Error Handling

Consistent Services Intern

Consistent Services

Developed an interactive 3D WAP-7 locomotive visualization in Unity/Unreal Engine with real-time animations, selectable components, and exploded views, integrating bilingual audio-visual training modules while adhering to RDSO/CLW technical standards.

Unity Unreal Engine 3D Visualization Exploded Views

Codec Technologies Intern

Codec Technologies

Built an end-to-end customer churn prediction model using Python and Scikit-learn, performing data preprocessing, feature engineering, model training and evaluation, and preparing the trained model for deployment with Joblib.

Python scikit learn Machine Learning data preprocessing Feature Engineering Model Training Model Evaluation