---
title: "PARTH ABHANG - Junior AI Engineer in Pune Division | Tal"
description: "Meet PARTH ABHANG, Junior AI Engineer at Flam based in Pune Division. AI stack includes claude code, hugging face, and notion. Explore public work links including github."
image: "https://tal.club/meet/parth-abhang/share-image"
---

# PARTH ABHANG on Tal

## Headline

Junior AI Engineer at Flam

## About

I’m a final year Computer Science student with a strong foundation in building intelligent, scalable applications\. I specialize in full\-stack development using React, Next\.js, FastAPI, and MongoDB, and work extensively with cloud platforms like AWS\. I’m passionate about machine learning and GenAI, with hands\-on experience using Langchain, Hugging Face, and LLMs to develop smart, adaptive systems\. I’m also deeply interested in blockchain, MLOps, and modern software engineering practices\.

## Location

Pune Division

## AI stack

claude code

hugging face

notion

ollama

ChatGPT

vLLM

## Work experience

Junior AI Engineer at Flam, Jun 2026 \- Present · 4 mos, Bengaluru, Karnataka, India

AI Intern at Flam, Aug 2025 \- May 2026 · 10 mos, Banglore

Software Engineer – AI Product Development at OpenLynks, Apr 2025 \- Aug 2025 · 5 mos, Hybrid, • Built end\-to\-end AI\-powered solutions to automate the entire supply chain lifecycle, from procurement to delivery\. • Worked with advanced LLMs including Claude and Command R for intelligent decision\-making and automation\. • Gained hands\-on experience with key AWS services such as Bedrock, RDS, SageMaker, OpenSearch, S3, and EC2\. • Designed and deployed AI agents on AWS Bedrock, trained on domain\-specific knowledge bases for accurate contextual responses\. • Developed a self\-service POC for clients that automated quotation workflows—fetching product enquiry emails, generating quotations, and enabling approval, all with minimal human intervention\. • Built interactive dashboards and portals to showcase agents and models using MERN stack and Streamlit, enhancing user interaction and visibility\.

Full Stack AI Intern at Supervaisor\.ai, Apr 2025 \- Aug 2025 · 5 mos, Remote, • Assisted in building a Retrieval\-Augmented Generation \(RAG\) application for RERA\-related document verification, enabling automated compliance checks using large language models\. • Contributed to training and fine\-tuning multiple AI models for tasks including human tracking, action detection, and anomaly detection in real\-time systems\. • Developed interactive frontends using Next\.js and React\.js to enhance user interaction with AI\-driven features\. • Supported the development and integration of FastAPI backends and Flask applications for seamless API communication and deployment\. • Designed and implemented a project to analyze advertisement effectiveness by comparing banner ad visibility with actual product enquiries, providing insights into conversion rates\. • Helped build a real\-time Chrome extension to scrape structured data from any e\-commerce webpage, using AI\-suggested fields, human prompt input, and click\-to\-select functionality\. \* Gained hands\-on experience with computer vision and ML frameworks such as YOLO, MMAction, and vector databases like Pinecone for semantic retrieval tasks\.

Frontend Developer and GenAI Engineer at The Squirrel, Jan 2025 \- Feb 2025 · 2 mos, Remote, Frontend Developer \| Crowdfunding Platform Development • Engineered and implemented responsive frontend architecture for a crowdfunding platform similar to AidCircle utilizing React\.js and Next\.js • Developed and integrated multiple complex UI components, enhancing user experience and donation flow • Collaborated with cross\-functional teams to ensure seamless integration between frontend interfaces and backend systems GenAI Developer \| Chatbot Enhancement • Enhanced performance and user interaction capabilities of an enterprise\-level chatbot system for technology platforms similar to SocialHardware • Integrated Retrieval\-Augmented Generation \(RAG\) pipelines, significantly improving response accuracy and relevance • Implemented efficient data retrieval mechanisms to ensure contextually appropriate responses • Optimized query processing time, reducing latency while maintaining high\-quality interactions

Research Assistant at Indian Institute of Information Technology Dharwad, Dec 2024 \- Apr 2025 · 5 mos, Hybrid, • Designed and implemented innovative approaches for sentence and concept ranking using semantic information retrieval rather than traditional lexical methods, resulting in more contextually accurate summaries\. • Pioneered lightweight optimization techniques \(LoRA/QLoRA\) for LLaMA 3 models, enabling efficient fine\-tuning while maintaining performance integrity\. • Developed sophisticated knowledge graph integration frameworks to enhance semantic understanding and representation in domain\-specific summarization tasks\. • Engineered dynamic topic modeling workflows that extract and analyze key concepts to produce concise, informative summaries from complex healthcare documentation\. • Created novel embedding visualization techniques using TensorBoard and Weight & Biases \(WandB\) to better understand semantic relationships between concepts\.

## Education

Bachelor of Technology \- BTech, Computer Science and Engineering, indian institute of information technology dharwad

JEE Mains and JEE Advanced, Bakliwal Tutorials

## Public links

- github: https://github\.com/Parth0124

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

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