---
title: "Rushil Chugh - Software Development Engineer II in Greater Bengaluru Area | Tal"
description: "Meet Rushil Chugh, ML Systems Engineer | Post-Training, Evals, VLMs | Amazon GenAI based in Greater Bengaluru Area. AI stack includes anthropic apis, antigravity, and claude code."
image: "https://tal.club/meet/rushil-chugh-1/share-image"
---

# Rushil Chugh on Tal

## Headline

ML Systems Engineer \| Post\-Training, Evals, VLMs \| Amazon GenAI

## About

I build machine learning systems for frontier\-model workflows i\.e\. post\-training, evaluation, reward design, VLMs, data curation, and inference\. My recent work spans production LLM/VLM systems, including post\-training, designing reward functions, building eval frameworks, and creating large\-scale data pipelines for foundation\-model training\. I am especially interested in post\-training, RL, VLMs, evals, synthetic data, data curation, and applied ML infrastructure\. I also built Veridis, a legal AI workspace, as a way to apply these ideas to real messy knowledge work: long documents, evidence retrieval, drafting workflows, evaluation, and human\-in\-the\-loop review\. Looking for frontier AI engineering roles where the work is close to models, data, evals, and product behavior\.

## Location

Greater Bengaluru Area

## AI stack

anthropic apis

antigravity

claude code

claude

codex

cursor

## Work experience

Software Development Engineer II at Amazon, Aug 2022 \- Present · 4 yrs 1 mo, Bengaluru, Built production AI and platform systems across GenAI, model workflows, evaluation, data pipelines, inference, and large\-scale consumer product infrastructure\. \- Worked on LLM/VLM workflows spanning post\-training, reward functions, evals, data curation, and inference optimization\. \- Built foundation\-model data pipelines with filtering, deduplication, and PII scrubbing\. \- Built eval and experimentation loops to measure performance of the developed and served model

Software Engineer at Paytm, Jul 2021 \- Jul 2022 · 1 yr 1 mo, India, Built data and search infrastructure for merchant intelligence over large\-scale payment streams\. \- Built Spark feature pipelines over merchant transaction streams \- Built Elasticsearch\-based similarity search for merchant segmentation using behavioral embeddings and ranking signals\. \- Reduced ML pipeline compute cost by 90% through Spark repartitioning, reusable feature snapshots, and parallelized backfills\.

Software Associate at JPMorgan Chase & Co\., Jan 2019 \- Jul 2021 · 2 yrs 7 mos, Built pricing, valuation, and cost\-optimization systems for financial derivatives workflows\. \- Developed a collateral pricing and valuation platform across collateral positions, haircuts, margin rules, and market\-data inputs\. \- Built workload and cost models for valuation runs, saving $400K\+ annually through better compute scheduling\.

[View the original profile](https://tal.club/meet/rushil-chugh-1)

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