AI Tech Lead at Pinterest, driving Growth products that power content discovery and shopping through LLM post training, AI agents, and Recsys.
Outside of work, I contribute to genomic sciences research at university labs, building LLMs for mRNA analysis with multiple publications in scientific journals.
Played a crucial part in user acquisition to reach millions of users worldwide. Scaling data platform, ML, and GenAI features to drive global growth:
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Led Pinterest's first GenAI production experiment on user activation and content enrichment, resulting in a significant 20% increase in traffic and a 60% boost in user engagement
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Identified and capitalized on opportunities to enhance the unauth user shopping initiative by building a shopping landing experience that prioritized trending searches, strong shopping intent, and showcased top product offerings. Achieved a 10% in quality sessions improvement and 80% shopping traffic growth.
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Designing and optimizing large-scale machine learning systems, including content ranking systems to spotlight Pinterest's top-tier content. This led to an 15% surge in traffic, 120M boost in WAU and highest content index rate from search engine in Pinterest history
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Designed and developed the Pinterest internal A/B testing experiment framework, which increased 30% engineers' weekly productivity across multiple teams
Developed a SmartRate API to select optimal shipping rates based on time-in-transit criteria, reducing costs by 15% for enterprise clients and processing over millions of requests daily with 99.99% uptime
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Engineered a high-throughput, fault-tolerant data pipeline using Kafka and Spark Streaming, processing 50TB+ daily shipping data with sub-second latency including live shipment tracking (200K events/sec peak)
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Optimized database performance for high-volume transaction processing: Implemented sharding and read replicas with efficient indexing strategies and query optimizations, reducing p99 query latency by 60%
