Distributed Readings

Training and evaluating AI models is resource-intensive, requiring significant human effort to generate quality training data and assess model outputs.

LinkedIn's legacy search infrastructure couldn't scale to handle growing query volumes and evolving relevance requirements across its platform.

LinkedIn's LLM-based ranking systems faced latency and throughput challenges when serving personalized results at scale.