Feb 2026 – Present · 1 mo · Noida, Uttar Pradesh, India

• • Working in the Adobe Genuine group's ML team to detect users using pirated copies of Adobe products and users involved in fraudulent activities that breach Adobe's policies.

Jul 2023 – Feb 2026 · 2 yrs 7 mos · Noida, Uttar Pradesh, India

• Developed an ML model to detect Account Sharing that has resulted in a 4%+ conversion rate into paid subscribers.
• Built a risk assessment engine to determine risk associated with users by assessing their association with attributes like email, IP, device, etc.
• Built ML models to detect other fraud abuses like Trial Abuse, Bot Abuse, etc.

Aug 2022 – Jul 2023 · 11 mos · Noida, Uttar Pradesh, India

• Developed Scraper Service that crawls the web and gathers online conversations related to piracy of Adobe applications across Torrents, Reddit, Google, YouTube, etc.
• Created models to identify and score the level of piracy in an online conversation/ webpage.
• Built business-relevant keyword extraction and segmentation models to ease the understanding of huge text blocks.

Feb 2021 – Jul 2022 · 1 yr 5 mos · Noida, Uttar Pradesh, India

• Developed desktop applications for Windows and macOS using C++ and Chromium Embedded Framework (CEF) to identify and notify users of non-genuine/pirated usage of Adobe products.
• Developed automated Release Engineering pipeline to generate builds for the desktop application on Jenkins.
• Transitioned the Intel-based macOS client to arm64 compatible client after the release of Apple Silicon architecture by Apple.

Jun 2019 – Jan 2021 · 1 yr 7 mos · Noida, Uttar Pradesh, India

• Worked on the C++ desktop application as part of the Adobe Genuine team to detect usage of pirated copies of Adobe apps.
• Developed ML model to detect fraud and leakage of Serial Numbers.
• Worked on the security and product hardening space to resolve multiple PSIRTs and prevent security vulnerabilities.
• Implemented sandboxing in the desktop services on Windows and macOS to harden the applications.