---
title: "Shivdeep Mishra - Machine Learning Engineer in Pune/Pimpri-Chinchwad Area | Tal"
description: "Meet Shivdeep Mishra, Machine Learning Engineer | I help companies build production-ready LLM & RAG systems with 94% accuracy | GenAI, PyTorch, NLP | MLOps | FastAPI based in Pune/Pimpri-Chinchwad Area."
image: "https://tal.club/meet/shivdeep/share-image"
---

# Shivdeep Mishra on Tal

## Headline

Machine Learning Engineer \| I help companies build production\-ready LLM & RAG systems with 94% accuracy \| GenAI, PyTorch, NLP \| MLOps \| FastAPI

## About

Machine Learning Engineer delivering production\-ready GenAI systems with deep expertise spanning LLMs, RAG pipelines, and NLP architecture across multiple production deployments\. I build and deploy ML models achieving 94% accuracy in real\-world classification, serving REST APIs handling live inference at scale for healthcare and enterprise clients\. What I Deliver: → Production LLM & RAG Systems: Hugging Face Transformers, LangChain, prompt engineering architectures that reduce false positives by 65% → Deep Learning Architecture: PyTorch, TensorFlow, custom CNN/Transformer models for NLP, predictive modeling → API Deployment: FastAPI, Flask, REST endpoints for real\-time ML inference with 86% test accuracy → MLOps Engineering: Reproducible pipelines, versioning, CI/CD, production\-aware systems — not notebooks, not toy demos Core Stack: Python \(primary\) \| PyTorch \| TensorFlow \| HuggingFace \| LangChain \| RAG \| FastAPI \| Flask \| AWS \| Git \| Docker My Approach: I treat ML engineering the same way a senior software engineer treats system design — with structure, scalability, and production\-readiness from day one\. My GitHub includes complete end\-to\-end systems: RAG\-based applications, full NLP pipelines, deployed inference endpoints\. I don't build experiments; I build production assets\. Recent Impact: • Spam detection system \(CNN \+ Transformer\): 83% generalization accuracy, 65% false positive reduction \[Unified Pvt Ltd\] • Heart rate prediction \(Linear Regression\): 78% accuracy on healthcare datasets, Flask API deployed \[Codec\] • Geospatial ML integration: 9\-day sprint mastering location\-based feature engineering \[ISRO Certification\] Roles I'm Seeking: ML Engineer \| AI Engineer \| NLP Engineer \| GenAI Engineer \| Machine Learning Scientist Full\-time / Internship / Contract — Remote \| Hybrid \| On\-site \(Bengaluru, Lucknow, Rajapur\) If you're building LLM\-powered products, scaling ML research to production, or need RAG systems that work — let's connect\. 📧 Email: shivdeepmi7080@gmail\.com 💻 GitHub: SHHIVDEEP310 📍 Location: Eiffel city Chakan ,pune → Open to whole world

## Location

Pune/Pimpri\-Chinchwad Area

## Work experience

Machine Learning Engineer at Codec, Jan 2026 \- Mar 2026 · 3 mos, Luknow, • Built predictive ML models using TensorFlow on healthcare datasets; developed heart rate prediction system with Linear Regression achieving 78% accuracy through feature selection and statistical analysis • Created Flask REST API for real\-time model inference and deployed locally for production use • Conducted model evaluation using accuracy, precision, recall, and F1\-score metrics

Machine Learning Engineer at Unified Private Limited, May 2025 \- Jul 2025 · 3 mos, Lucknow, Engineered a spam detection system using CNN \+ Transformer architecture \(PyTorch\) that reduced false positives by 65%, improving classification reliability for production email pipelines\. Optimized via hyperparameter tuning to achieve 83% generalization accuracy on unseen data\. • Built customer churn prediction model using machine learning algorithms achieving 86% test accuracy with hyperparameter tuning and cross\-validation techniques • Performed data cleaning, exploratory data analysis, feature engineering, and comprehensive model evaluation

## Education

B\-tech, Computer Science, SHRI RAMSWAROOP MEMORIAL UNIVERSITY

[View the original profile](https://tal.club/meet/shivdeep)

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