Experienced ML Software Engineer with 10+ years of expertise in designing data-centric machine learning systems that drive business value by aligning technical and business needs. Recognized for hands-on experience in ML engineering, designing AI-enabled systems, and applied research expertise. Over the years, I've co-founded multiple companies, channeling my deep knowledge of ML foundations and practical engineering skills into building impactful AI-driven solutions.Predictive AI: With a PhD in predictive modeling and recommendation systems, I have developed, deployed, and scaled systems that serve millions of users with minimal latency and high accuracy. My work with startups Traxnet and Tapsell introduced adaptive, predictive models that process billions of feedback data points to continuously enhance user experience. These platforms utilize highly optimized models capable of handling millions of requests with only a few milliseconds of latency, delivering real-time personalization at scale.Generative AI: I have a deep understanding of the foundations of Generative AI, staying up-to-date with the rapid advancements in this field over the last two years. As co-founder of Tapsage, I built various end-to-end generative AI solutions across multiple domains, directly addressing the practical challenges of productionizing Gen-AI. This hands-on experience has given me a clear perspective on developing robust, scalable Gen-AI systems that meet real-world demands and integrate seamlessly into business workflows.With a strong focus on applied ML research and advanced system design, I’m passionate about developing scalable ML pipelines, predictive models, and robust deployment strategies that address real-world challenges.