---
title: "Ayushi Maheshwari - CS1 in Bengaluru | Tal"
description: "Meet Ayushi Maheshwari, Software Engineer @ Adobe Premiere Pro | IIIT-H Alum | C++ · JS · GenAI · High-Performance Video Systems based in Bengaluru. AI stack includes antigravity, codex, and cursor."
image: "https://tal.club/meet/ayushi-maheshwari/share-image"
---

# Ayushi Maheshwari on Tal

## Headline

Software Engineer @ Adobe Premiere Pro \| IIIT\-H Alum \| C\+\+ · JS · GenAI · High\-Performance Video Systems

## About

I build AI\-powered video features for Adobe Premiere Pro — used by millions of professional editors and filmmakers worldwide\. Over 3\+ years at Adobe, I've shipped production features that moved real numbers: · Reduced manual rotoscoping by \~90% via GPU\-accelerated AI Object Masking · Contributed to a 2% MAU increase across Premiere Pro through multi\-language Captions Translation · Cut manual audio tagging by \~90% with an Automatic Audio Category Tagger at 100% telemetry coverage My work spans low\-level C\+\+ systems, on\-device AI inference, full\-stack JavaScript/React integrations, and cross\-functional AI feature delivery from scoping to production\. Now exploring Senior SDE roles in AI\-powered product engineering, media tech, or developer tools where I can own systems end\-to\-end and lead high\-impact teams\.

## Location

Bengaluru

## AI stack

antigravity

codex

cursor

## Work experience

CS1 at Adobe, Jan 2024 \- Present · 2 yrs 8 mos, Bengaluru, Karnataka, India, • Engineered AI Object Masking in C\+\+, reducing manual rotoscoping by \~90% while preserving real\-time playback\. • Led the end\-to\-end Captions Translation integration using C\+\+, JavaScript, and React, driving a 2% growth in MAU\. • Drove on\-schedule delivery of AI features across multiple Premiere Pro releases, aligning product, research, and platform teams while mentoring junior engineers\.

Member of Technical Staff at Adobe, Jul 2022 \- Present · 4 yrs 2 mos, Reduced manual video rotoscoping by \~90% \- measured by QA benchmark tests across 500\+ clips \- by engineering AI Object Masking in C\+\+ with GPU\-accelerated on\-device inference with zero regression in real\-time playback performance\. Increased MAU by 2% by leading end\-to\-end Captions Translation \(C\+\+, JavaScript, React\), designing OOP abstractions to fully decouple translation logic from the UI layer and shipping across 10\+ locales\. Cut manual audio\-tagging effort by 90% and improved audio organisation accuracy by 30% — validated via A/B telemetry at 100% instrumentation coverage — by building the Automatic Audio Category Tagger with concurrency\-optimised inference and enforcing best\-practice code reviews across the team\.

MTS1 at Adobe, Jul 2022 \- Jan 2024 · 1 yr 7 mos, Bengaluru, Karnataka, India, • Developed Premiere Pro's Automatic Audio Category Tagger, significantly reducing manual audio tagging effort by \~90%\. • Implemented concurrency optimizations and Jenkins CI/CD pipelines to enhance audio organization by 30%\. • Achieved full automation of a previously manual editorial workflow, streamlining processes for better efficiency\.

Research Intern at Adobe Research Labs, May 2021 \- Jul 2021 · 3 mos, Achieved 2% improvement in entity extraction F1\-score on low\-resource domains — validated across 3\+ domain\-specific benchmarks — by designing and running experiments on one\-shot learning techniques \(prototypical networks, in\-context prompting\) to adapt NLP models with minimal labelled data, directly reducing annotation effort by \~40%\. Systematically compared few\-shot vs\. fine\-tuned baselines through controlled ablation studies, identifying one\-shot transfer as the optimal trade\-off between annotation cost and accuracy; findings informed domain\-adaptive interface design adopted by downstream research and engineering teams\.

Research Intern at ISRO, RRSC\-West, Jun 2019 \- Jul 2019 · 2 mos, Reduced visitor check\-in time significantly and handled 100\+ daily visitors at peak load — verified through stakeholder UAT — by designing and implementing a concurrent, multilingual Visitor Management System \(Python, Django, SQL, JavaScript\) with role\-based authentication, scheduling, and pass generation across 3\+ languages\.

## Education

Master of Technology, Computer Science, International Institute of Information Technology Hyderabad \(IIITH\)

BE \- Bachelor of Engineering, Computer Science, M\.B\.M\. Engineering College, Jodhpur

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

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