May 2024 – Present · 2 yrs 1 mo

• Leading and developing AI Strategies for multiple products in the company.
• Working with Image and Video Diffusion models like Stable Diffusion and Flux for Fashion and Product Photoshoot Generation Suite for Reliance Trends. Training various visual models to automate photography and videography.
• Implementing LLM and RAG pipelines in every product to transition all the company's products to be AI-first.
• Writing Evaluation Pipelines for LLM systems with real world monintoring and bechmarking across multiple LLM providers
• Working with the robotics team to implement computer vision-based shopping carts and plenogram verification machines
• Implementing ML Product Management and Data Governance strategies to centrally govern multiple ML teams and large sources of data
• Working on Computer Vision, LLMs and predictive ML including commerce ML related ones for optimising marketing and sales on e-commerce sites using AI assistance
• Launched BharatDiffusion to create India's own image foundation models

Jun 2021 – May 2024 · 2 yrs 11 mos

• Leading the research and engineering team of PixelBin, a A.I transformation and content delivery platform. Using the latest in LLMs and Image Generative Models to build cool products.
• → Launched multiple AI solutions, including erase.bg, upscale.media, Diffusion Background Generator, Product Tagging, and image enhancement, achieving 250k daily traffic and 6.8M monthly visits and surpassing 1M$/year in ARR.
• → Oversaw a research team of 7 in implementing CNNs, Diffusion models, and Transformers for various computer vision applications
• → Managed a 4-person engineering team responsible for deployment infrastructure serving 250k daily users, optimizing scaling and cost with TensorRT and AWS Inferentia
• → Established a 4-member 3D artist team leveraging Blender for synthetic data creation and 3D work
• > Worked on a number of computer vision problems like super-resolution, object tracking, 3d vision and GAN based models
• > Involved in deep learning research and optimising costs + lowering inference time of model deployments.

Oct 2019 – Aug 2021 · 1 yr 10 mos

• Fynd AML Research: research.fynd.com
• EraseBG: https://erase.bg
• Core team member and principal researcher for EraseBG, a completely automated background removal service
• Created data collection pipeline integrating active learning approaches
• Lead the machine learning/deep learning/computer vision research required for the task of foreground identification and transparency prediction(Image Matting)
• Built a robust solution from scratch that can handle a huge variety of cases
• Took part in business decisions to create a Product Led Growth strategy for the product
• Worked on object detection and tracking for retail store video analytics platform Fynd Trak
• Implemented various metric learning approaches for visual recommendation search engine
• Read about what EraseBG does: https://bluesky314.github.io/bgremoval/
• 2 Research Publications:
• AlphaNet: An Attention Guided Deep Network for Automatic Image Matting
• IEEE publication: https://ieeexplore.ieee.org/document/9191371
• Arvix Pre-print: https://arxiv.org/abs/2003.03613
• Salient Image Matting (Currently in peer-review)
• Arvix Pre-print: https://arxiv.org/abs/2103.12337
• EraseBG is live on https://erase.bg
• Check out our ProductHunt launch: https://www.producthunt.com/posts/erase-bg