Ge Gao

Contract role focusing on designing a unified data storage layer and ML/LLM infrastructure for cloud-native distributed systems. Led cross-cloud (AWS, Azure, GCP) data workflows, metadata governance, and end-to-end RLHF training pipelines. Implemented performance optimizations, MLflow integration, and contributed to reliability improvements. Mentored junior engineers and guided large-scale pipeline orchestration.

Core backend engineer on Google Cloud Storage (GCS) with responsibilities for multi-region replication, cross-region consistency, and scalable storage pipelines. Led efforts in metadata tooling, data integrity checks, and deployment automation, delivering reductions in RPC latency and improved throughput across distributed deployments. Collaborated with multiple teams including Spanner for joint reliability and performance initiatives.

Spanner team contributor focused on transaction coordination and replication. Built simulation frameworks for cross-data-center clock drift, reduced RPC latency, and designed distributed metadata catalogs and routing. Implemented live debugging tooling and reliability improvements, contributing to increased system resilience.