A Uniquely Interactive Experience

Why MLOps Production & Engineering?

Too few companies have effective AI leaders or an effective AI strategy.

An interactive conference is one in which you meet attendees before the event, message speakers directly, discuss specific areas of your work and establish a stronger network. We’re working to help you with a clearer understanding of best practices, methodologies, and principles of effective ML.

The micro-summit includes:

  • 16 Speakers
  • 4 Workshops

Join this new initiative to help push the AI community forward.

We’re Hosting

BREAKOUT SESSIONS
(All Levels)

DISCUSSION GROUPS

WORKSHOPS

VIRTUAL PLATFORM

Speakers

Sai Xiao

Machine Learning Engineer, Pinterest

Bio & Abstract

Talk: Shopping Recommendations at Pinterest

Amit Paka

CPO & Co-founder, Fiddler AI

Bio & Abstract

Talk: Build High Performance MLOps With ML Monitoring and AI Explainability

Jennifer Prendki

Founder and CEO, Alectio

Bio & Abstract

Talk: Data Prep Ops: The Last Frontier of ML Ops

Auro Tripathy

Technical Marketing Manager, Tenstorrent

Bio & Abstract

Talk: A Gentle Introduction to Sparsity with A Concrete Example

Deepak Pai

Senior Manager, Machine Learning, Adobe

Vijay Srivastava

Manager, Machine Learning, Adobe

Bio & Abstract

Talk: Automated Monitoring in Production for Continuous Model Improvements

Danny Luo
Machine Learning Engineer, Nextdoor
Bio & Abstract

Talk: Running ML Inference Services in Shared Hosting Environments

Reah Miyara
Head of Product, Arize AI
Bio & Abstract

Talk: ML Observability: A Critical Piece in the ML Stack

Ville Tuulos

CEO, Co-Founder, Outerbounds

Bio & Abstract

Talk: Human-Centric MLOps: Why Productivity Matters the Most

Mike Berg
Vice President, Technology in Admin, AltaML
Bio & Abstract

Talk: The Ops In MLOps

Shivam Bharuka
Senior AI Infra Engineer, Facebook
Bio & Abstract

Talk: Machine Learning Infrastructure at Facebook Scale

Stacey Svetlichnaya

Deep Learning Engineer, Weights & Biases

Bio & Abstract

Talk: Reproducible Machine Learning: How (Not) to Repeat the Past

Betty Zhang
Data Scientist, Amazon Web Services (AWS)
Bio & Abstract

Talk: How to Iterate and Productionize Machine Learning Models with Speed

Alessya Visnjic

CEO, WhyLabs

Bio & Abstract

Talk: The Critical Missing Component in the Production ML Stack

Ashwini Badgujar
Machine Learning Engineer, Impulse Logic
Bio & Abstract

Talk: End-to-end MLOps for Computer Vision

Workshop Facilitators

Adam Gugliciello
Senior Solutions Engineer, Dataiku
Bio & Abstract
Workshop: MLOPs with Dataiku: Considerations For Model Deployment & Monitoring
Jimmy Whitaker

Data Science Evangelist, Pachyderm

Bio & Abstract

Workshop: Intro to MLOps: Build, Deploy, and Retrain a Model in Production

Yaron Haviv

Co-Founder and CTO, Iguazio

Bio & Abstract
Workshop: Accelerating Deployment of AI with MLOps Orchestration
Mohamed Sabri
Consultant in MLOps, Rocket Science
Bio & Abstract
Hands-on Workshop: Create Machine Learning Retraining Pipelines
More to be announced
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