I am a Machine Learning Engineer with a strong focus on building scalable AI systems, optimizing large models, and translating cutting-edge research into real-world impact. At Apple, I’ve led the development of agentic LLM systems, distributed training pipelines, and cloud-agnostic ML platforms that significantly accelerate model iteration, reduce costs, and improve product quality across Maps Search. My background spans federated learning, computer vision, and model efficiency, with several publications in top conferences such as ACM RecSys and IEEE venues. I've previously contributed to large-scale experimentation systems at Facebook, secure federated learning research at USC ISI, and data-driven analytics at Schlumberger. With a foundation in computer science from USC (MS) and MIT Pune (BE), I’m passionate about designing intelligent, robust, and efficient machine learning solutions that solve complex problems at scale.