---
title: "RAHUL YALAVATTI - Generative AI Engineer in Greater Bengaluru Area | Tal"
description: "Meet RAHUL YALAVATTI, Data Scientist @ Kenvue | NLP & Generative AI | Python, PyTorch, Transformers | Building Production ML Pipelines based in Greater Bengaluru Area. AI stack includes claude, langchain, and langgraph."
image: "https://tal.club/meet/rahul-yalavatti/share-image"
---

# RAHUL YALAVATTI on Tal

## Headline

Data Scientist @ Kenvue \| NLP & Generative AI \| Python, PyTorch, Transformers \| Building Production ML Pipelines

## About

As a Data Scientist at Kenvue, I develop and deploy NLP\-driven solutions to address business challenges at scale\. My current focus is on creating a Bill of Materials \(BOM\) Cross\-Reference pipeline using fine\-tuned RoBERTa embeddings and multi\-method similarity scoring, achieving 88% match coverage\. I also diagnosed and resolved production issues affecting multi\-component record matching and implemented a confidence\-boosting layer using logistic regression and TF\-IDF for improved accuracy\. I hold a Bachelor of Technology in Electronics and Communications Engineering from Jain \(Deemed\-to\-be University\)\. My technical expertise spans Python, PyTorch, Transformers, and LangChain, with experience in building and maintaining ML pipelines on Azure ML using CI/CD\. Passionate about leveraging AI, NLP, and machine learning to solve real\-world problems, I am open to connecting with professionals working on advanced AI/ML applications\.

## Location

Greater Bengaluru Area

## AI stack

claude

langchain

langgraph

openai

githubcopilot

Chroma

## Work experience

Generative AI Engineer at Kenvue, Jan 2026 \- Present · 10 mos, Bengaluru, \- Developed an NLP pipeline to automatically match ERP and TRU \(Product 360\) Bill of Materials records using fine\-tuned RoBERTa embeddings and multi\-method similarity scoring, achieving 88% match coverage\. \- Diagnosed and fixed a production bug causing silent match failures for multi\-component records \(front/back labels\), building a custom rescue\-matching function that recovered lost matches without impacting existing logic\. \- Implemented an ML\-based confidence\-boosting layer \(Logistic Regression \+ TF\-IDF\) that improved high\-confidence match rates by up to 15%\. \- Deployed and maintained the pipeline on Azure ML with CI/CD via Jenkins\.

Software Engineer at Happiest Minds Technologies, Aug 2023 \- Jan 2026 · 2 yrs 6 mos, Bengaluru, Karnataka, India · Hybrid, • Developed and deployed hybrid recommendation engine combining collaborative filtering and content\-based algorithms, improving user engagement metrics and click\-through rates \. • Implemented matrix factorization techniques \(SVD, NMF\) and deep learning models using TensorFlow to process 2M\+ user interactions and generate personalized recommendations\. • Engineered comprehensive feature extraction pipeline handling user behaviour patterns, item metadata, and temporal features, improving recommendation accuracy by 25%\. • Containerized application using Docker and deployed on AWS EC2 with auto\-scaling capabilities\. • Implemented CI/CD pipeline using GitHub Actions for automated testing, model validation, and deployment, reducing deployment time\.

Engineer Trainee at Happiest Minds Technologies, Aug 2023 \- Feb 2024 · 7 mos, Bengaluru, Karnataka, India · Hybrid

## Education

Bachelor of Technology \- BTech, Electronics and Communications Engineering, Jain \(Deemed\-to\-be University\)

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

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