Bio
Jacqueline Wood is a Staff Machine Learning Engineer at Spotify, where she builds personalized, language-steerable generative recommenders. Her applied research focuses on adapting open-weight LLMs with semantic IDs to connect natural-language intent with Spotify catalog entities.
Session (1)
Additional Speaker Details
Using publicly available information we constructed an analysis to help you get a feel for this speaker before deciding to attend their session.
Jacqueline Wood works on Spotify's generative-recommendation systems — she's a co-author on Spotify's GLIDE (podcast discovery) and NEO (unified search/recommendation) papers and co-presented on domain-adapting open-weight LLMs with semantic IDs at Netflix's 2025 PRS workshop, so her session should offer a grounded, production-tested view of LLM-based recsys rather than a purely theoretical one.