3rd Annual MLOps World Conference on Machine Learning in Production

June 7th – 10th 2022, Toronto Canada

2022 Tickets will be Open Soon


A Uniquely Interactive Experience

3rd Annual MLOps World Conference on Machine Learning in Production

Join our community of over 9,000 members as we learn best practices, methods, and principles for putting ML models into production environments.

Why MLOps? Read more

MLOps World will help you put machine learning models into production environments; responsibly, effectively, and efficiently.

We’ll be covering topics such as

  • Version Management
  • CI/CD Architecture for Model Deployment
  • Pipeline Scheduling Optimizations
  • Feature Engineering
  • Feature Store Design and Maintenance
  • Effective Data/Machine Learning Strategies
  • New Research
  • And more!

Come share your stories and join us June 7-10th

Each Pass includes:

Community Networking

Receive invites to meet with the wider Community via Slack today

Demo Days

Learn current tools / open source projects from specialists at Demo Days
June 8th – 10th


Post jobs, see applicants / register as a job-seeker

Upskill Workshops

Conference workshops begin
June 14th – 15th

Conference Sessions

Interactive sessions. Exclusive Case studies
June 16th – 17th

Past Speakers Include


Talk: Catch Me If You Can: Keeping Up With ML Models in Production

Shreya Shankar
ML engineer, PhD student
Jules Damji

Talk: The AI Captain; A study of ML at the Edge

Rob High
Vice President and CTO, IBM Networking and Edge Computing, IBM Fellow
Matei Zaharia

Talk: Productionizing Machine Learning at Scale with MLflow

Matei Zaharia
Chief Technologist, Databricks and Assistant Professor, Stanford

Each Ticket Includes Learning Workshops:

Some may have limited seating. Ask about our team discounts


13jun11:00 AM3:00 PMHands-On Workshop: How to Build Pipelines with KubeflowMohamed Sabri - Senior Consultant in MLOps, Rocket Science11:00 AM - 3:00 PM

14jun9:00 AM10:25 AMWorkshop: Productionize with Kubeflow Orchestration with Feast in GCPAniruddha Choudhury - Senior Datascientist, Publicis Sapient9:00 AM - 10:25 AM

14jun11:00 AM12:00 PMWorkshop: Fixing Data Quality at Scale with Data ObservabilityBarr Moses - CEO & Co-Founder & Lior Gavish - Co-Founder, Monte Carlo11:00 AM - 12:00 PM

14jun11:00 AM12:30 PMHands-On Workshop: Advanced Model Deployment with Seldon Deploy: Deploying a Customer Segmentation Model; Configuring Drift, Outlier Detection & Model ExplainabilityTom Farrand - Lead Solutions Engineer & Sean Greaves - Lead Solutions Engineer, Seldon11:00 AM - 12:30 PM

14jun12:00 PM2:00 PMIguazio Presents: MLOps Orchestration: Your Highway to Accelerating Deployment of AIYaron Haviv - Co-Founder and CTO, Iguazio12:00 PM - 2:00 PM

14jun1:00 PM2:00 PMWorkshop: MLOps with PyCaretMoez Ali - Founder and Author, PyCaret1:00 PM - 2:00 PM

14jun1:00 PM2:30 PMHands-On Workshop: Complete ML Lifecycle with MLflow: Learn its Four ComponentsJules S. Damji - Senior Developer Advocate, Databricks, Inc. 1:00 PM - 2:30 PM

14jun3:00 PM7:25 PMWorkshop: From Concept to Production: Template for the Entire ML JourneyChanchal Chatterjee - Artificial Intelligence Leader & Elvin Zhu - AI Engineer & Timothy Ma - ML Specialist, Google3:00 PM - 7:25 PM

14jun4:00 PM5:30 PMModelOp Presents: Building a Model Life Cycle: The First Step in Operationalizing AI Models (Bonus Workshop)Jim Olsen - CTO, ModelOp4:00 PM - 5:30 PM

15jun9:00 AM1:30 PMWorkshop: Essential Workshop to Exploratory Data Analysis and Feature EngineeringVladimir Rybakov - Head of Data Science & Aleksandr Mester - Data Scientist, WaveAccess9:00 AM - 1:30 PM

15jun9:00 AM10:00 AMWorkshop: Long Live Models: A Tutorial on Model Monitoring in ProductionEmeli Dral - CTO / Co-founder & Elena Samuylova - CEO / Co-Founder, Evidently AI9:00 AM - 10:00 AM

15jun9:00 AM1:00 PMWorkshop: Good, Fast, Cheap: How to Do Data Science with Missing DataMatthew Brems - Managing Partner & Principal Data Scientist, BetaVector9:00 AM - 1:00 PM

15jun11:00 AM1:00 PMWorkshop: Building an ML Platform from ScratchAlon Gubkin - VP R&D, Aporia11:00 AM - 1:00 PM

15jun11:00 AM12:30 PMWorkshop: Closing the Production Gap with MLOpsAsger Pedersen - ML Worldwide Technical Lead, DataRobot11:00 AM - 12:30 PM

15jun1:00 PM1:45 PMMLOPs with Dataiku: Considerations For Model Deployment & MonitoringChristina Hsiao - Senior Product Marketing Manager, Dataiku1:00 PM - 1:45 PM

15jun1:00 PM4:00 PMSensibill Presents: Deploying an E2E ML Pipeline with AWS SageMaker - What Amazon Didn't Tell You (Bonus Workshop)Kollol Das - ML Research Lead & Fred Caroli - ML Research Lead, Sensibill1:00 PM - 4:00 PM

15jun1:00 PM5:25 PMWorkshop: From Concept to Production: Template for the Entire ML JourneyChanchal Chatterjee - Artificial Intelligence Leader & Elvin Zhu - AI Engineer & Timothy Ma - ML Specialist, Google1:00 PM - 5:25 PM

15jun3:00 PM4:30 PM5 Governance Capabilities You Need in MLOpsTrey Morrow - Solutions Engineers & Dwayne Dreakford - Solutions Engineer, Algorithmia3:00 PM - 4:30 PM

15jun3:00 PM5:00 PMTaking Aim at Bias in AI - How 10 Companies learned to Audit, Investigate and Mitigate Bias in AI ModelsShingai Manjengwa & Rishav Agarwal & Fatemeh Darbehani & Michael Skupien & Tomas Tokar & Bart Gajderowicz3:00 PM - 5:00 PM

June 16th – 17th Exclusive Interactive Sessions:


16jun10:30 AM11:00 AMIs Your ML Model Trustworthy?María Grandury - Machine Learning Research Engineer, Neurocat GmbH10:30 AM - 11:00 AM

16jun10:30 AM11:00 AMConnecting Data Scientists to Production with the Tempo Python SDKClive Cox - CTO, Seldon10:30 AM - 11:00 AM

16jun10:30 AM11:00 AMIntegrating Multiple MLOps Tools Together on Google Cloud PlatformMefta Sadat - Senior ML Engineer, Loblaw Digital10:30 AM - 11:00 AM

16jun11:05 AM11:35 AMData Scientist or ML Engineer: Who Do We Need Now?Marcin Mizianty - Vice President, Data Science, AltaML11:05 AM - 11:35 AM

16jun11:05 AM11:35 AMBreaking the Monolithic ML Pipeline with a Feature StoreJim Dowling -  CEO,  Logical Clocks and Associate Professor, KTH Royal Institute of Technology11:05 AM - 11:35 AM

16jun11:05 AM11:35 AMMachine Learning Tools: Skyline and RL-ScopeGennady Pekhimenko - University of Toronto / Vector Institute11:05 AM - 11:35 AM

16jun11:40 AM12:10 PMFrom 12 Months to 30 Days to AI Deployment: An MLOps JourneyYaron Haviv - Co-Founder and CTO, Iguazio & David Aronchik - Partner, Product Manager, Azure Innovations Group in the Office of the CTO, Microsoft & Greg Hayes - Data Science Director, Ecolab11:40 AM - 12:10 PM

16jun11:40 AM12:10 PMDeveloping a Data-Centric NLP Machine Learning PipelineDiego Castaneda - Data Scientist & Jennifer Bader - Content Strategist, Shopify11:40 AM - 12:10 PM

16jun11:40 AM12:10 PMFLAML: Fast and Lightweight AutoMLChi Wang - Principal Researcher & Qingyun Wu - Postdoc Researcher, Microsoft Research11:40 AM - 12:10 PM


16jun12:30 PM1:00 PMProductionizing Machine Learning at Scale with MLflowMatei Zaharia - Chief Technologist, Databricks and Assistant Professor, Stanford12:30 PM - 1:00 PM


16jun1:05 PM1:35 PMDesign Patterns for MLOpsSara Robinson - Senior Developer Advocate, Google Cloud1:05 PM - 1:35 PM

16jun1:05 PM1:35 PMModel Monitoring: What, Why, and HowManasi Vartak - CEO, Verta Inc1:05 PM - 1:35 PM

16jun1:05 PM1:35 PMSystematic Approaches and Creativity: Building DoorDash's ML Platform During the PandemicHien Luu - Sr. Engineering Manager & Dawn Lu - Data Scientist, DoorDash1:05 PM - 1:35 PM

16jun1:05 PM1:35 PMProject MagLev: An MLOps Platform for Autonomous Vehicles Development at NVIDIANicolas Koumchatzky - Senior Director, AI Infra, Nvidia1:05 PM - 1:35 PM

16jun1:40 PM2:25 PMMachine Learning on Dynamic GraphsEmanuele Rossi - Machine Learning Researcher, Twitter1:40 PM - 2:25 PM

16jun1:40 PM2:25 PMThe AI Captain; A study of ML at the EdgeRob High - Vice President and CTO, IBM Networking and Edge Computing, IBM Fellow1:40 PM - 2:25 PM

16jun1:40 PM2:25 PMFiddler AI Presents: Data and Process Governance for Responsible and Ethical AIKrishna Gade - CEO & Co-Founder, Fiddler AI1:40 PM - 2:25 PM

16jun2:45 PM3:15 PMHoloClean and Kamino: Structured Learning for Private Data GenerationIhab Ilyas - Professor, University of Waterloo2:45 PM - 3:15 PM

16jun2:45 PM3:15 PMMLOps Platform Architecture for E2E ML PipelinesJoao Da Silva - Lead Data Engineer, Avast2:45 PM - 3:15 PM

16jun2:45 PM3:15 PMCatch Me If You Can: Keeping Up With ML Models in ProductionShreya Shankar - ML Engineer, PhD Student2:45 PM - 3:15 PM

16jun3:20 PM3:50 PMSecurity Audits for Machine Learning AttacksNavdeep Gill - Lead Data Scientist/Team Lead, Responsible AI & Michelle Tanco - Customer Data Scientist, H2O.ai3:20 PM - 3:50 PM

16jun3:20 PM3:50 PMThe Critical Missing Component in the Production ML StackAlessya Visnjic - CEO and Co-Founder, WhyLabs3:20 PM - 3:50 PM

16jun3:20 PM3:50 PMMarius: Machine Learning Over Billion-Edge Graphs 10x Faster and 5x CheaperTheodoros Rekatsinas - Assistant Professor, University of Wisconsin-Madison3:20 PM - 3:50 PM

16jun3:55 PM4:25 PMChallenges for ML Operations in a Fast Growing CompanyGulsen Kutluoglu - Director of Engineering & Sam Cohan - Principal ML Engineer, Udemy3:55 PM - 4:25 PM

16jun3:55 PM4:25 PMQuick Deploy Model Serving in Ranking SystemsTalal Riaz - Software Engineer, ML Infrastructor, Yelp Inc.3:55 PM - 4:25 PM

16jun3:55 PM4:25 PMMLOps vs. ModelOps – What’s the Difference and Why You Should CareJim Olsen - CTO, ModelOp3:55 PM - 4:25 PM


17jun10:30 AM11:00 AMHow Not to Let Your Data and Model Drift Away SilentlyChengyin Eng - Data Science Consultant, Databricks10:30 AM - 11:00 AM

17jun10:30 AM11:00 AMMLSecOps and Shift-Left Your Security Gears in Model LifecycleArun Prabhakar - Senior Consultant, Security Compass10:30 AM - 11:00 AM

17jun10:30 AM11:00 AMProduction Machine Learning Monitoring: Outliers, Drift, Explainers & Statistical PerformanceAlejandro Saucedo - Engineering Director, Seldon10:30 AM - 11:00 AM

17jun11:05 AM11:35 AMMachine Learning Optimizations and Strategy for Post-Covid EraSharmistha Chatterjee - Senior Manager Data Sciences, Publicis Sapient11:05 AM - 11:35 AM

17jun11:05 AM11:35 AMBreaking Down Scotiabank's New Global AI PlatformPooja Bhojwani - Senior Data Scientist & Min Li - Director IB AIML, Scotiabank11:05 AM - 11:35 AM

17jun11:40 AM12:10 PMMLOps at Acerta: Automation of the Machine Learning Life Cycle for ManufacturingAmit Jain - Director Machine Learning & Harika Gaggara - Data Scientist, Acerta Analytics11:40 AM - 12:10 PM

17jun11:40 AM12:10 PMScale-Out-First Microarchitecture for Efficient AI ComputeJasmina Vasiljevic - Director Software Engineering, Tenstorrent11:40 AM - 12:10 PM

17jun11:40 AM12:10 PMTinyML and Efficient Deep LearningSong Han - Assistant Professor, MIT11:40 AM - 12:10 PM


17jun12:30 PM1:00 PMTaking AIM at Racial and Language Bias in AI Models; How 10 Companies learned to Audit, Investigate and Mitigate Bias in AI ModelsShingai Manjengwa - Director of Professional Development, Vector Institute & Godwin Liu - Industrial Technology Advisor, National Research Council of Canada (NRC), IRAP Ontario Region12:30 PM - 1:00 PM


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2020 Event Demographics


Currently Working in Industry*


Attendees Looking for Solutions


Currently Hiring


Attendees Actively Job-Searching

2020 Technical Background

  • Expert 17.7% 17.7%
  • Advanced 37.1% 37.1%
  • Intermediate 35.1% 35.1%
  • Beginner 9.7% 9.7%

2020 Attendees have included:

Account Coordinator
Account Executive
Account Manager
AI & ML Lead
AI Architect
AI Devleoper
AI Engineer
AI Product Manager
AI Research Lead
Engineering Manager – ML Platform
Executive Data Scientist & Delivery Executive
Finance Assistant
Founder & CEO
Front-End Engineer
Fullstack Developer
Graduate Student
Head of Data & ML
Head of Data Science
Senior Big Data Platform Engineer
Senior Business Systems Analyst
Senior Computer Vision and Machine Learning Engineer
Senior Consulting Analyst
Senior Data Analyst
Senior Data Engineer
Senior Data Manager
Senior Data Research Scientist
Senior Data Scientist
Senior Data Scientist – Supply Chain

2020 Companies have included

Amazon Web Services
Analytics For Life Inc
Bayer Crop Science
Bell Canada
GoodLabs Studio
Government of Canada
Grid AI
Hewlett Packard Inc
Hitachi, Ltd.
PyTorch Lightning
Radical Ventures
Toronto Raptors
Royal Bank of Canada
Red Hat