---
title: "Rishabh Shah - Software Engineer in Mumbai | Tal"
description: "Meet Rishabh Shah, AI Engineer | LLM Systems, RLHF, Evaluation Pipelines | Experience on Gemini (via Turing) | IIT Madras based in Mumbai. AI stack includes claude code, codex, and langfuse. Explore public work links including github."
image: "https://tal.club/meet/rishabh-shah/share-image"
---

# Rishabh Shah on Tal

## Headline

AI Engineer \| LLM Systems, RLHF, Evaluation Pipelines \| Experience on Gemini \(via Turing\) \| IIT Madras

## About

Data Scientist \(3\+ yrs\) with experience in developing ML and analytical models across healthcare and technology domains\. M\.Tech in Data Science from IIT Madras with a strong foundation in statistics, probability, and optimization\. Passionate about quantitative research and financial markets, applying data science methods like time series analysis, LSTM modeling, and portfolio optimization to real\-world data\. Skilled in Python, NumPy, Pandas, PyTorch, SQL, AWS, Git, and Spark\.

## Location

Mumbai

## AI stack

claude code

codex

langfuse

langgraph

ollama

opencode

## Work experience

Software Engineer at Harmoney, Dec 2025 \- Jun 2026 · 6 mo, Mumbai, Maharashtra, India

Data Scientist at Turing, May 2024 \- Dec 2025 · 1 y 7 mo, Mumbai, Maharashtra, India, Worked on Google’s Gemini project \(via Turing\), building large\-scale LLM systems focused on reasoning, reliability, and evaluation\. • Built agentic workflows and evaluation pipelines to assess LLM reasoning and robustness across diverse tasks • Applied SFT and RLHF techniques to improve model performance, increasing accuracy from 12% to 44% on curated benchmarks • Designed simulation environments for API\-driven and multimodal tasks, enabling scalable and reproducible testing • Developed quantitative evaluation frameworks for model consistency, edge\-case behavior, and failure analysis • Co\-led cross\-functional efforts across 15\+ engineers to deliver ML modules and evaluation systems at scale

Senior Data Scientist at HiLabs, Jan 2024 \- May 2024 · 5 mos, Bengaluru, Karnataka, India, Optimized Provider Directory Accuracy and Attribution Outlier Detection systems, focusing on explainable time series modeling and scalable production efficiency\. \* Built anomaly detection models \(SARIMA, ARIMA, LSTM\) to monitor shifts in provider attribution; adopted SARIMA for its interpretability\. \* Improved entity\-resolution by using DOM\-based proximity logic, enhancing accuracy of provider\-linkage mapping\. \* Migrated modules to PySpark, cutting execution time and reducing AWS compute costs by 20%\. \* Deployed ML pipelines with monitoring and explainability safeguards for production readiness\.

Data Scientist at HiLabs, Jul 2022 \- Dec 2023 · 1 yr 6 mos, Pune District, Maharashtra, India, Developed ML and NLP modules for HiLabs’ Provider Directory Accuracy platform — improving data integrity and automated entity resolution across large\-scale provider datasets\. \* Built ARIMA, SARIMA, and neural network models to detect attribution anomalies, reducing false positives by 30%\. \* Applied spaCy NER and proximity\-based algorithms to extract and link provider attributes from unstructured web pages\. \* Created a multi\-class XGBoost model using BERT embeddings, achieving 93% precision for website classification\. \* Designed structured schemas linking providers to attributes like address and specialty for improved validation\.

Data Scientist at Saint\-Gobain Research India, May 2021 \- Apr 2022 · 11 mo, Chennai, Tamil Nadu, India, As a part of my Master's Thesis, collaborated with Saint\-Gobain Research India and RBCDSAI, IIT Madras to enhance induction furnace performance through predictive modeling and optimization\. The project applied industrial data science techniques to improve process efficiency and operational reliability\. \* Built XGBoost, PORT, and Neural Network models on high\-frequency sensor data to predict optimal operating parameters\. \* Developed a Genetic Algorithm–based optimization framework, improving solver speed by 3× and enhancing interpretability\. \* Implemented time series and regression models for performance forecasting and real\-time monitoring\. \* Bridged academic and industrial collaboration by translating research prototypes into deployable optimization workflows\.

Summer Intern at Anheuser\-Busch InBev, May 2021 \- Jul 2021 · 3 mos

## Education

Inter Disciplinary Dual Degree \(IDDD\), Data Science, Indian Institute of Technology, Madras

Bachelor of Technology \- BTech, Naval Architecture and Ocean Engineering, Indian Institute of Technology, Madras

## Public links

- github: https://github\.com/shah\-rishabh

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

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