Atul is a Technical Leader specializing in Generative AI, Computer Vision, and Edge AI. With extensive experience in building and deploying AI solutions at scale, he focuses on bridging the gap between cutting-edge research and practical applications. He excels in solving critical problems across various domains, including Financial Technology, Autonomous Checkout, Autonomous Vehicles, and Digital Health, leveraging advanced techniques in Generative AI, Computer Vision (CV), Machine Learning (ML), Deep Neural Networks (DNN), and Edge AI. His passion lies in developing scalable, large-scale ML products.

Key Achievements

  • Led the safe and secure adoption of Generative AI tools at PayPal, boosting developer productivity by 30% within select Analytics and Data Science teams.
  • Scaled autonomous checkout systems at Standard Cognition from 2 to 40+ stores, reducing costs by $4M YoY through comprehensive ML model lifecycle development. Delivered a next-generation Edge AI hardware platform, enabling cost-effective scaling to the next 100 stores with projected margin improvements of $1M per store annually.
  • Independently designed and selected Edge compute for a fully autonomous (L4) platform at NIO, laying the foundation for the Adam supercomputer.

Areas of Expertise

  • Generative AI: Development, deployment, and fine-tuning of large language models and generative systems for diverse applications
  • Computer Vision: Deep learning solutions for visual recognition, scene understanding, and object detection
  • Edge AI: Optimization, deployment, and inference of ML models on edge devices with hardware constraints
  • Autonomous Systems: Development of perception algorithms for autonomous platforms
  • Retail Analytics: Creation of trajectory-based and visual feature-based analytics solutions to enhance operational efficiency and user engagement
  • ML Infrastructure: Architecting scalable systems for automated training, deployment, and management of machine learning models
  • Leadership & Strategy: Team building, mentorship, roadmap planning, and driving cross-functional collaboration for AI and ML projects