---
title: "Jaiprasad Reddy (JP) - Agentic Lead in Hyderabad | Tal"
description: "Meet Jaiprasad Reddy (JP), RL Lead @ Deccan AI | Post training, SFT, RLHF, LLM Evals, RL Gym based in Hyderabad."
image: "https://tal.club/meet/jaiprasad-reddy/share-image"
---

# Jaiprasad Reddy \(JP\) on Tal

## Headline

RL Lead @ Deccan AI \| Post training, SFT, RLHF, LLM Evals, RL Gym

## About

AI Architect \| Full Stack AI \| LLM \| MLOps \| AI Agents \| RAG With a solid foundation in data science and over 9\+ years of experience, I excel in devising and deploying innovative AI solutions across a spectrum of industries such as e\-commerce, agri\-tech, and healthcare\. My expertise encompasses a broad range of technologies including computer vision, natural language processing, machine learning, deep learning, Large Language Models \(LLMs\), Retrieval\-Augmented Generation \(RAG\), and Generative AI\. I adeptly apply these technologies to complex problems, achieving breakthroughs in classification, detection, segmentation, and generative tasks\.

## Location

Hyderabad

## Work experience

Agentic Lead at Deccan AI, Mar 2026 \- Present · 7 mos, Hybrid, After building internal pipelines, now leading everything related to coding, RL , agentic client fulfilments: \- Leading E2E projects from data collection process, platform development to training models for client data shipment\.

ML Lead at Deccan AI, Aug 2025 \- Apr 2026 · 9 mos, \- Built multiple features to streamline the sourcing, assessment and fitment\.

Data science at Mensa Brands, Nov 2022 \- Aug 2024 · 1 yr 10 mos, Abu Dhabi, Abu Dhabi Emirate, United Arab Emirates, Data science \| MLOps

Principal Data Scientist at Johnson Controls, Feb 2021 \- Aug 2022 · 1 yr 7 mos, Bangalore Urban, Karnataka, India, \- Engineered a multi\-tenant architecture for the business logic layer, dramatically reducing inference time by 10x, and significantly enhancing system efficiency and performance\. \- Advanced the object detection system from single\-class to multi\-class detection and tracking, broadening the module's capabilities and application scope\. \- Acted as a pivotal member of the design committee for a next\-generation AI platform, contributing to strategic planning and innovative solutions\.

Data Scientist at MFine, Mar 2019 \- Mar 2021 · 2 yrs 1 mo, Bengaluru, Karnataka, India, \- Designed and developed a MLOps infrastructure from scratch, optimizing AI model management, resulting in a 50% reduction in re\-training time and a 75% decrease in AWS costs\. Achieved rapid production deployment and comprehensive tracking, shortening the POC to production cycle to just 3 days, utilizing Metaflow and AWS Services for complete ML lifecycle management\. \- Developed AI models to automate case report section suggestions for junior doctors, reducing their workload by 20% and enhancing report accuracy\. \- Contributed to a variety of projects, including fundus grading, development of an ML visualization library, X\-Ray analytics, and initiatives to optimize doctor workload, demonstrating versatility and impact across healthcare AI applications\.

Data Scientist \- IV at SigTuple, Dec 2018 \- Mar 2019 · 4 mos, Bengaluru Area, India, \- Led the OCT analysis clinical study for DME classification, achieving key milestones in medical imaging research\. \- Developed and managed the Dipstick Analyzer project, overseeing everything from synthetic data collection to model development for 7\-parameter analysis, including innovative image normalization and clustering algorithms\.

Senior Computer Scientist at SigTuple, Feb 2018 \- Dec 2018 · 11 mos, Bengaluru, Karnataka, India, \- Revolutionized DR grading with a novel CNN, enhancing classification and detection, leading to two successful clinical studies and AI service deployment\. \- Led DME OCT scan classification, achieving a clinical study milestone before strategic discontinuation\. \- Obtained a patent for a groundbreaking enhancement in CNN architecture for DR/OCT analysis\. \- Integrated Unet architecture into the AI platform, enabling advanced segmentation model training\.

Computer Scientist at SigTuple, Mar 2017 \- Jan 2018 · 11 mos, Bengaluru, Karnataka, India, \- Revamped WBC extraction with a Computer Vision algorithm, boosting recall from 60% to 98%, pivotal in a major clinical trial's success\. Published findings at MICCAI 2017\. \- Overhauled WBC screening and classification models, employing diverse architectures and visualization techniques to rectify misclassifications and enhance data quality, resulting in a 34% performance increase\. \- Led rigorous testing and optimization of 100\+ model variations, achieving a significant leap in accuracy to 96%, demonstrating a committed, iterative approach to model enhancement\.

## Education

Bachelor of Technology \(B\.Tech\.\), Electrical and Electronics Engineering, National Institute of Technology Karnataka

Karnataka Pre University Board, Applied Sciences, Diamond PU Science College

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

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