---
title: "Sarthak Shinde - AI/ML & Data Science Intern in Pune/Pimpri-Chinchwad Area | Tal"
description: "Meet Sarthak Shinde, AI/ML Engineer | Python Developer | GenAI, RAG & Computer Vision | FastAPI • LangChain • OpenCV | Open to Full-Time Roles 2026 based in Pune/Pimpri-Chinchwad Area. AI stack includes antigravity, claude, and codex. Explore public work links including github."
image: "https://tal.club/meet/sarthak-shinde/share-image"
---

# Sarthak Shinde on Tal

## Headline

AI/ML Engineer \| Python Developer \| GenAI, RAG & Computer Vision \| FastAPI • LangChain • OpenCV \| Open to Full\-Time Roles 2026

## About

Most AI/ML projects die in Jupyter notebooks\. Mine went into production at Tata Motors — and I've kept building since\. I'm Sarthak — a final\-year Computer Science student who doesn't just build models, I ship systems that replace manual work with automation\. THE PROBLEM I SOLVED AT TATA MOTORS: Trainee assessments were 100% paper\-based — 1,000\+ records, manual entry, zero analytics\. I built an OCR \+ ML pipeline \(OpenCV \+ Tesseract \+ FastAPI, Dockerized\) that digitized the entire workflow, improved extraction accuracy by 25%, and moved reporting for 10\+ stakeholders from weekly Excel updates to real\-time dashboards — cutting evaluation cycle time by 70\-80%\. WHAT I'VE BUILT SINCE: A RAG\-based document Q&A system \(LangChain \+ Gemini \+ ChromaDB\) that lets users query PDFs in natural language with page\-level source citations A no\-code analytics platform \(Streamlit \+ Scikit\-learn\) that automates full data science workflows for non\-technical users An NLP \+ clustering pipeline segmenting 10,000\+ financial records into trader behavior archetypes WHAT I ACTUALLY DO: GenAI & NLP: RAG pipelines, LLM integration, prompt engineering, vector search Computer Vision: OCR systems, OpenCV preprocessing, image\-to\-data extraction ML Development: Regression, classification, clustering, model deployment Backend Engineering: FastAPI, Docker, REST APIs, scalable ML endpoints I don't chase Kaggle scores\. I build systems that ship\. MY STACK: Languages: Python, SQL GenAI/NLP: LangChain, Hugging Face, Transformers, Prompt Engineering ML/AI: Scikit\-Learn, TensorFlow, PyTorch, Pandas, NumPy Computer Vision: OpenCV, Tesseract OCR Frameworks: FastAPI, Flask, Streamlit DevOps: Docker, Git/GitHub, CI/CD, REST APIs WHAT I'M LOOKING FOR: AI/ML Engineer, Data Scientist, or GenAI Engineer roles starting 2026\. I want to join teams that: Ship ML/AI systems to production, not just POCs Value clean code and reproducibility Measure impact in business metrics, not just model accuracy If you're building AI that matters, let's talk\. shindesarthak36@gmail\.com

## Location

Pune/Pimpri\-Chinchwad Area

## AI stack

antigravity

claude

codex

## Work experience

AI/ML & Data Science Intern at Tata Motors, Oct 2025 \- Jan 2026 · 4 mos, Pimpri Chinchwad, Designed and deployed a production\-grade OCR and ML analytics pipeline that automated manual trainee assessment workflows — processing 1,000\+ unstructured paper records and cutting evaluation cycle time by 70\-80%\. OCR PIPELINE DEVELOPMENT \- Architected an end\-to\-end digitization system \(OpenCV \+ Tesseract \+ Python\), converting 1,000\+ paper records into structured, analysis\-ready datasets \- Engineered a custom preprocessing chain \(Gaussian denoising → adaptive binarization → multi\-pass normalization\), improving OCR accuracy by 25% \- Eliminated the fully manual data entry process — the largest bottleneck in the evaluation workflow MACHINE LEARNING & ANALYTICS \- Built and validated regression and K\-Means clustering models in Scikit\-Learn with 5\-fold cross\-validation \- Performed EDA and feature engineering across 5\+ training cohorts, improving training effectiveness scores by 15% \- Applied statistical validation to ensure model reliability before handoff to reporting PRODUCTION DEPLOYMENT & ENGINEERING \- Deployed a Dockerized KPI reporting platform \(FastAPI \+ REST APIs\), shifting dashboards for 10\+ stakeholders from weekly Excel updates to real\-time access — eliminating a 7\-day reporting lag \- Built a modular, Git\-versioned codebase with independently testable components for reproducibility and future scaling \- Automated the full workflow end\-to\-end: ingestion → preprocessing → modeling → reporting IMPACT: Replaced a manual, paper\-based process with a Dockerized, real\-time ML system — cutting cycle time 70\-80%, improving accuracy 25%, and giving 10\+ stakeholders real\-time visibility\. TECH: Python • OpenCV • Tesseract • Scikit\-Learn • FastAPI • Docker • Pandas • NumPy • Git • REST APIs

## Education

Bachelor of Technology, Computer Engineering, Nutan College of Engineering & Research

## Public links

- github: https://github\.com/sarthak7\-securtiy

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

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