---
title: "Prem Borse - LLM fine tuning Intern in Dhule Rural | Tal"
description: "Meet Prem Borse, Full Stack & AI Developer | React · Python · LLMs | Built MEDIASSIST AI (Award-winning) | 2× Intern | B.Tech CSE 2027 | Open to Paid Internships based in Dhule Rural. AI stack includes langgraph, mastra, and perplexity."
image: "https://tal.club/meet/prem-borse/share-image"
---

# Prem Borse on Tal

## Headline

Full Stack & AI Developer \| React · Python · LLMs \| Built MEDIASSIST AI \(Award\-winning\) \| 2× Intern \| B\.Tech CSE 2027 \| Open to Paid Internships

## About

I'm a Computer Engineering student \(DBATU, 2027\) who has shipped real products across two stipend internships — from LLM fine\-tuning pipelines at an early\-stage AI startup \(Ethara AI\) to full\-stack client projects at Blue Planet Info Solutions\. My flagship project is MEDIASSIST AI — an award\-winning rural healthcare platform I built independently using Google AI Studio \(Gemini API\), Python, React, and FastAPI\. It won competitions across Maharashtra and serves users with limited healthcare access through: → ML\-based symptom analysis → Medical report summarization → Handwritten prescription digitization → Doctor appointment booking 🛠 Stack: Python · React · TypeScript · FastAPI · SQL · Google AI Studio · Gemini API · LLMs · Azure ML · N8n · Vercel I work best in small teams where I can own a feature end\-to\-end, pick up new tools fast, and ship things that real users depend on\. 🔍 Actively seeking a paid Full Stack or AI internship \(₹15,000–₹20,000/month\) — open to remote and onsite\. 📩 premborse99@gmail\.com

## Location

Dhule Rural

## AI stack

langgraph

mastra

perplexity

replit

## Work experience

LLM fine tuning Intern at Ethara AI, Jan 2026 \- Mar 2026 · 3 mos, Gurugram, Haryana, India, Stipend\-based internship at an early\-stage AI startup working on LLM fine\-tuning pipelines\. \- Collected, cleaned, and structured domain\-specific datasets to prepare training data for large language model \(LLM\) fine\-tuning pipelines\. \- Annotated and validated thousands of data samples to ensure quality and consistency across training sets\. \- Collaborated with the ML team to iterate on data quality processes, directly impacting model training cycles\. \- Performed Exploratory Data Analysis \(EDA\) to identify patterns and inconsistencies in raw datasets before processing\. \- Worked with Python and data processing tools in a fast\-moving startup environment with real production timelines\. Tools & Tech: Python · LLMs · Data Annotation · EDA · Data Processing

## Education

Bachelor of Technology \- BTech, Computer Engineering, Dr\. Babasaheb Ambedkar Technological University \(DBATU\)

[View the original profile](https://tal.club/meet/prem-borse)

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