Diya Khetarpal

About Diya Khetarpal

Hi, I’m Diya, a final-year student at Maharaja Agrasen Institute of Technology, passionate about building impactful solutions at the intersection of AI, machine learning, and software engineering. Over the course of my journey, I’ve worked on diverse projects across generative AI, natural language processing, computer vision, and no-code ML platforms. I have hands-on expertise in LangChain, LangGraph, and PyTorch, along with experience in vector databases (Milvus, Pinecone, Weaviate), cloud services (AWS Bedrock), and edge AI systems (Jetson, Dockerized microservices). I’m also an open-source contributor to SunPy (6.1 release), where I collaborated with the global developer community to improve scientific computing tools. Beyond technical skills, I thrive in team environments, bringing creativity and problem-solving to projects that matter. Some highlights of my journey so far: Top 6 finalist in Google Girl Hackathon, recognized for building an innovative ML-based healthcare solution. Selected in top 10 teams out of teams who applied for Campus Beats ZS Selected among top 500 out of people for AWS AIML nanodegree program based on theme Future Data Engineer I love to explore emerging AI frameworks, push the limits of what’s possible with LLMs and generative AI, and translate complex research into real-world applications. Always eager to collaborate on innovative ideas and contribute to the growing AI ecosystem.

Experience

1. Generativeai Intern

   Etech Global Services

   Apr 2025 — Present · TX, US

   As a Generative AI Intern at eTech Global Services, I had the opportunity to work on multiple cutting-edge AI projects that combined natural language processing, information retrieval, and large language model integration.I contributed to the development of a Personal Information Redaction Bot, designed to automatically detect and redact sensitive data from text, ensuring compliance with data privacy requirements. I also worked on building a Recruitment Bot to streamline candidate interaction and hiring processes, as well as a Knowledge Base Chatbot that leveraged Retrieval-Augmented Generation (RAG) for accurate and context-driven responses from ingested organizational data.During this internship, I gained hands-on experience with vector databases like Milvus, Pinecone, and Weaviate, optimizing retrieval performance for large-scale embeddings. I also explored AWS Bedrock for deploying and experimenting with foundation models, integrating them into scalable AI-driven solutions.This role gave me practical exposure to the end-to-end lifecycle of generative AI applications, from data ingestion and retrieval pipelines to model deployment and real-world use cases. It sharpened my ability to solve business problems using AI and strengthened my skills in LLM fine-tuning, RAG pipelines, and cloud-based AI services.

Education

• Maharaja Agrasen Institute Of Technology, Delhi

  Bachelor of Technology - BTech

  2022 — 2026

• Shree kali devi vidya mandir hansi

  12th Non Med

  2012 — 2022