Unconference: AI Engineering that Delivers

From the same track

Session

Dynamic Moments: Weaving LLMs into Deep Personalization at DoorDash

In this talk, we’ll walk through how DoorDash is redefining personalization by tightly integrating cutting-edge large language models (LLMs) with deep learning architectures such as Two-Tower Embeddings (TTE) and Multi-Task Multi-Label (MTML) models.

Speaker image - Sudeep Das

Sudeep Das

Head of Machine Learning and Artificial Intelligence, New Business Verticals @DoorDash, Previously Machine Learning Lead @Netflix, 15+ Years in Machine Learning

Speaker image - Pradeep Muthukrishnan

Pradeep Muthukrishnan

Head of Growth for New Business Verticals @DoorDash, Previously Founder & CEO @TrustedFor, 15+ Years in Machine Learning

Session

From Reinforcement Learning Enhanced Image to AI Collection Generation: How Pinterest Cracked the Code on Content Discovery

his talk presents Pinterest's journey in deploying AI at massive scale, from using Reinforcement Learning to create images to building 

Speaker image - Faye Zhang

Faye Zhang

Staff Software Engineer @Pinterest, Tech Lead on GenAI Search Traffic Projects, Speaker, Expert in AI/ML with a Strong Background in Large Distributed System

Session

Automating the Web With MCP: Infra That Doesn’t Break

AI agents are only as strong as the infrastructure beneath them. In this talk, we’ll walk through the architecture behind Browserbase’s model context protocol (MCP), built to support stateful browser automation at scale.

Speaker image - Paul Klein

Paul Klein

Founder @Browserbase, previously Director of Self-Service & Engineering Manager @Mux, Co-Founder & CTO @Stream Club, Technical Lead @Twilio Inc.

Session

Building Large Scale AI: Image to Video & Immersive Experiences

Details coming soon.

Session

How to Build Enterprise-Aware Agents

Details coming soon.