Yue Yao

Worked on high-throughput Java/Kafka backend systems and production services. Improved recommendation retrieval latency by replacing scan-heavy logic with scalable filtering, delivered via replay validation, feature-flag rollout and monitoring (latency 210ms -> 80ms), reduced index build time and CPU usage. Led migration from a legacy serving engine to a service-oriented backend architecture with modular services, compatibility layers and RPC contracts using replay testing and staged monitoring, with no major incidents or revenue regression and enabled monetisation uplift. Enhanced production observability by converting Druid metrics into actionable anomaly alerts with baseline comparisons, dynamic thresholds and alert grouping to reduce triage time from ~30 minutes to 5–10 minutes. Maintained Kafka event processing pipelines (multi-billions events/day) with encryption, validation, deduplication rules, anti-fraud API integration, checkpointing/offset tracking and reliability metrics.