GenRec: Towards LLM-Native Recommendation at Netflix

What this post added

This post introduces GenRec, an LLM-backed recommendation ranker that leverages Netflix's LLM serving infrastructure. It details the two-phase training framework (Netflix-adapted foundation LLM and GenRec post-training), the conversion of interaction logs into conversational data for training, and the crucial 'context engineering' techniques used to manage prompt token budgets. It also outlines the multi-objective loss function, combining catalog-aware ranking, language modeling, and reward-weighted loss for alignment with business goals and long-term member satisfaction. The post highlights the use of vLLM in prefill-only mode for cost efficiency.