I'm a Machine Learning Engineer and Applied Scientist passionate about building practical AI systems that bridge research and production.

My interests include:

• 🤖 Large Language Models (LLMs)
• 👁️ Computer Vision & Multimodal AI
• 🎨 Generative AI
• ⚡ Efficient ML systems and inference
• 📊 Machine Learning infrastructure and optimization

I contributed to TensorFlow Similarity helping improve TensorFlow's metric learning library by implementing multiple optimized loss functions. Also contributed some PRs as part of Google Summer of Code.

🔗 https://github.com/tensorflow/similarity

An AI-powered analytics platform for exploring Swiggy order history. The project combines LLMs, structured data analysis, and interactive visualizations to generate personalized insights, answer natural language queries, and uncover ordering trends from a user's food history.

A framework for generating realistic synthetic document datasets for OCR. It supports customizable document layouts, fonts, backgrounds, and annotations to create large-scale training data for document understanding and OCR models.

I'm always interested in building AI systems that move beyond research into production. My repositories span LLM applications, computer vision, multimodal learning, generative AI, ML infrastructure, and open-source contributions.