• Product features for next generation of Radio Experience
• Backend storage system for efficient retrieval and querying of listener's spin information
• Designed and implemented a feature store for ML runtime systems
• Lead developer for recommender systems for offline radio
• Introduced Apache Spark at Pandora
• Designed and implemented several pipelines in spark and responsible for maintaining and setting up recommendation systems Spark Cluster
• Content and collaborative recommendation systems for Music
• Large scale fingerprinting of music for integration with labels and music providers
• Developed Thumbprint Radio station service backend, Pandora's largest listened to station
• Backend and data pipelines for several personalized, content and collaborative filtering based recommenders