About Me
With over 17+ years of experience in ML/AI, I have developed large-scale machine learning and deep learning models across various domains, including retail, FMCG, search relevance, computational advertising, and voice assistants. I have led technical efforts on improving speech recognition and language understanding at Amazon Alexa and building Contextual Advertising at Amazon Ads. At Alexa, I built personalized, self-healing error correction foundation models that learn from daily user interactions—enabling run-time query rewriting with speculative execution for low-latency, high-throughput inference on accelerated hardware. My technical leadership in research and applied science spans early adoption of state-of-the-art research into ML products, driving science efficiency and accelerating innovation. I have worked on SOTA research applications in LLMs, Multimodal LLMs, RAG, Agents and Congitive Architecture.
I am recognized for my first-principles thinking and a constant-learning mindset, qualities that have consistently led to innovative and unconventional solutions to challenging problems. Additionally, I have advised early-stage startups in the advertising and healthcare space. I love reading books (non-fiction), hiking outdoors, landscape/astro photography, and spending time with family.
Past Life: Management Consultant for a Fortune-50 CPG Pharma advising one of the world's largest loyalty program rollouts.
