Rakesh Sunki is an accomplished engineering leader with over 13 years of expertise in search ranking, machine learning, and large-scale distributed systems. His career has focused on developing AI-driven solutions that enhance search relevance, recommendation systems, and user engagement. He has a proven track record of designing scalable and impactful systems, driving technological innovation, and improving operational efficiency in globally recognized companies.
Currently, as an Engineering Lead at Apple Inc. (since October 2020), Rakesh has led significant initiatives such as improving the search ranking quality for Apple Maps, developing deep learning-based models to enhance place discovery, and pioneering a recommender system to mitigate cold-start issues. His efforts have resulted in a 20-40% improvement in search ranking accuracy and user satisfaction. Rakesh has also made substantial contributions to Apple Wallet and Maps integration, enhancing transaction matching accuracy with machine learning models.
Before Apple, Rakesh served as a Senior Software Engineer at Qualcomm (2011-2017), where he was instrumental in developing Wi-Fi Aware technology for Android and the AirDrop file-sharing system for macOS. His work in peer-to-peer communication and device interoperability has set the foundation for improved Android connectivity features and efficient macOS file transfers.
Rakesh holds an MS in Computer Science from the University of Southern California and a BE in Electrical Engineering from Osmania University. His technical expertise spans Java, Scala, C++, and C programming, along with specialized knowledge in search engine ranking, machine learning, distributed systems, and A/B experimentation.
Notable achievements include a publication on "BAYESCNS: A Unified Bayesian Approach to Address Cold Start and Non-Stationarity in Search Systems at Scale" and presentations at AAAI 2025 and BayLearn 2024 conferences. He has been recognized with multiple Qualcomm Qualstar Awards for excellence in product development and delivery.