Panel: MLOps - Production & Delivery for ML Platforms

From the same track

Session Machine Learning

Improve Feature Freshness in Large Scale ML Data Processing

Wednesday Jun 14 / 11:50AM EDT

In many ML use cases, model performance is highly dependent on the quality of the features they are trained and inference on. One of the important dimensions of feature quality is the freshness of the data.

Zhongliang Liang

Engineering Manager @Facebook AI Infra

Session MLOps

Platform and Features MLEs, a Scalable and Product-Centric Approach for High Performing Data Products

Wednesday Jun 14 / 04:10PM EDT

In this talk, we would go through the lessons learnt in the last couple of years around organising a Data Science Team and the Machine Learning Engineering efforts at Bumble Inc.

Massimo Belloni

Data Science Manager @Bumble

Session AI/ML

Building Production AI-Powered Applications with the OpenAI API and Plugins

Wednesday Jun 14 / 02:55PM EDT

We recently introduced Chat Completions into the OpenAI API – which currently powers the GPT-4 and ChatGPT APIs.

Sherwin Wu

Technical Staff @OpenAI

Atty Eleti

Software Engineer @OpenAI

Session ML Infrastructure

Introducing the Hendrix ML Platform: An Evolution of Spotify’s ML Infrastructure

Wednesday Jun 14 / 10:35AM EDT

The rapid advancement of artificial intelligence and machine learning technology has led to exponential growth in the open-source ML ecosystem.

Divita Vohra

Senior Product Manager @Spotify

Mike Seid

Tech Lead for the ML Platform @Spotify


Unconference: MLOps

Wednesday Jun 14 / 01:40PM EDT

What is an unconference? An unconference is a participant-driven meeting. Attendees come together, bringing their challenges and relying on the experience and know-how of their peers for solutions.