Criteo x NVIDIA AI Developer Meetup | LLM-Powered Recommendations at Scale
Overview
Join NVIDIA and Criteo to hear how teams take LLM-powered recommendations from prototype to production. Learn what it really takes to deliver relevance at scale, from inference stack design to optimizing open-weight models on-premises, with candid lessons from the builders.
Agenda
6:00 PM - Door openings
6:30 PM - Welcoming Remarks by Criteo and Nvidia
6:45 PM - How to Build a High-Throughput, Low-Latency Product Relevance Classifier On-Premises w/ Criteo
7:15 PM - Advancing Generative Recommendation Inference w/ NVIDIA
7:45 PM - Panel Discussion
8:15 PM - Networking, food and drinks
Sessions
Advancing Generative Recommendation Inference
Marek Pikulski, Senior AI Developer Technology Engineer, NVIDIA
Learn how NVIDIA and Spotify engineered a production-grade inference stack for LLM-powered personalized recommendations. This talk covers the specific challenges of running beam search, multi-item candidate scoring, and user soft token injection at scale, and how native support for these patterns was built into TensorRT LLM. We’ll walk through the architecture decisions, open-source contributions, and the benchmarks that made the case for the switch.
How to Build a High-Throughput, Low-Latency Product Relevance Classifier On-Premises
Zakaria Ouzarf, Software Development Engineer, Criteo
Marius Alonso, Machine Learning Engineer, Criteo
How can you build an open-weight LLM-based product relevance classifier that matches the performance of a frontier model—entirely on-premises? We’ll share our journey building a relevance classifier for agentic recommendations, covering fine-tuning, distillation, quantization, and inference optimization, along with the wins, dead ends, and hard numbers.
Panel
Zakaria Ouzarf, Software Development Engineer, Criteo
David Lacalle, Senior ML Engineer, Photoroom
Marek Pikulski, Senior AI Developer Technology Engineer, NVIDIA
Moderated by: Matt Groshong, Director Business Development, NVIDIA
Resources and Legal
Resources
NVIDIA Privacy Policy: https://www.nvidia.com/en-us/about-nvidia/privacy-policy/
Criteo Privacy Policy: https://www.criteo.com/privacy/