TWIMLcon

On Demand

Learn How the Experts Deliver
High-Velocity Machine Learning
at Scale!

Learn How the Experts Deliver High-Velocity Machine Learning at Scale!

In its second year, TWIMLcon: AI Platforms 2021 again assembled an impressive selection of enterprise ML/AI practitioners and leaders for two weeks of insightful presentations, workshops and discussions on accelerating ML development and deployment in the enterprise.

Experience the best of this event with TWIMLcon On Demand, and learn from nearly 60 speakers and 40 sessions, including interviews with data science, ML and AI leaders like:

Fran Bell in Collared jacket outdoors
Executive Summit
Keynote
VP, Head of Data and Analytics
bp
Faisal Siddiqi Netflix
Keynote
Director of Engineering, Personalization Infrastructure
Netflix
Solmaz Shahalizadeh Shopify
Keynote
Vice President, Commerce Intelligence
Shopify
Chris Albon
Keynote
Director of Machine Learning
WikiMedia
Ya Xu
Keynote
Head of Data Science
LinkedIn

The application of machine learning in the enterprise is moving incredibly fast, with modeling techniques, platforms, tools, frameworks, and infrastructure all evolving rapidly. As a result, many organizations are failing to get the most out of their ML investments, due to the many challenges of moving ML models from development to production.

Ten years from now we will look back on this period of time with wonder: Why did we struggle so hard to operationalize ML models? Why were there so many tool choices and platform options? Why was everyone building their own platforms and tools? Why was it so hard to incorporate best practices like MLOps?

Unfortunately, those organizations that opt to wait for clarity may not be around to benefit from it when it arrives! The rest of us must roll up our sleeves and figure out how to efficiently stand up the people, processes and platforms that will allow us to deliver ML and AI at scale.

At TWIMLcon: AI Platforms, we gathered world-class experts—practitioners and leaders who are building tools and teams for delivering high-velocity ML and AI at scale—to share their thoughts on some of the questions that we all find ourselves wrestling with.

With your TWIMLcon On Demand pass, you will learn:

Order your TWIMLcon On Demand pass and don’t miss a single session.

As a TWIMLcon On Demand pass holder, you will have access to over 20 hours of content from 56 world-class practitioners on any device—laptop, tablet or smartphone.

There is no reason to make the same mistakes that have already been made. Learn from those who have come before you and who are succeeding in building some of the world’s largest AI/ML systems and teams.

Learn from industry leaders and skip the learning curve.
Get TWIMLcon On Demand and get started now!

A Masterclass in Delivering High-Velocity ML at Scale

With over 30 sessions, TWIMLcon On Demand offers a masterclass in how to design and build teams and platforms for delivering machine learning in a high-velocity, repeatable, consistent and predictable manner—at scale:

Twimlcon
“The benefits of attending this conference have been immeasurable. I learned how MLOps and the right machine learning platforms can take teams to the next level, but also that it isn’t just about the tools — it's also about how you instill the team's culture within the platform itself.
Mitchell Wade
Sr. Data Scientist Exelon Corp

A masterclass in delivering enterprise ML & AI.
Order TWIMLcon On Demand today!

Build Smarter, Innovate Faster and Avoid Costly Mistakes

TWIMLcon sessions—presented by data scientists, engineers and leaders from teams at the forefront of operationalizing machine learning—can help you and your team save time and money by learning:

Order TWIMLcon On Demand now.
Packages start at $499 $399

Learn What Works and What Doesn't When Building for Scale and Velocity in the Real World

Faisal Siddiqi Netflix

Faisal Siddiqi

Director of Engineering, Personalization Infrastructure

Netflix

Faisal is the Director of Engineering for Personalization Infrastructure at Netflix, where he runs multiple teams delivering large-scale ML infrastructure to support the company’s personalization research and systems. The teams he runs currently support model development, model tools and data, and model serving. In this keynote conversation, Faisal and Sam discuss lessons learned building Netflix’s large-scale personalization infrastructure.
solmaz in ruffled shirt

Solmaz Shahalizadeh

Vice President, Commerce Intelligence
Shopify
Solmaz is the Vice President of Data Science & Engineering at Shopify. During her time there, she has implemented the company’s first ML products, built their financial data warehouse, led multiple cross-functional teams, and played a critical role in their IPO. In this keynote interview, Sam and Solmaz discuss how she’s helped the company scale its use of machine learning and how that has helped power the company’s growth.

Chris Albon

Director of Machine Learning
WikiMedia
Chris Albon joined the Wikimedia Foundation in 2020 as director of machine learning with a mandate to empower the teams producing models for Wikipedia to move more quickly. In this keynote interview, Sam and Chris discuss ML use cases at Wikimedia, the evolution of the organization’s ML infrastructure, their use of Kubernetes and Kubeflow to support the ML workflow, and their ultimate plans to make this infrastructure available to the broader Wikimedia community.

Ya Xu

Head of Data Science
LinkedIn
Ya Xu leads the LinkedIn data science practice, consisting of hundreds of researchers distributed across the USA (Sunnyvale, Mountain View, San Francisco, New York), India and Dublin. The team touches every aspect of the organization, helping to inform decisions about new product features, business investments, surfacing economic insights for policy makers, and much more. In this keynote interview, Sam and Ya explore her career transition from a platform-oriented role to one focused on data science products, the horizontal tools and capabilities her team maintains, and some of the ways her team is innovating in areas like experimentation, privacy and fairness.

Build your ML Operationalization Knowledge Through Case Studies, How-Tos, Perspective Talks, Panels and Workshops

SELECT SESSIONS

How Spotify Does ML at Scale

Spotify
Aman Khan Spotify

Aman Khan

Product Manager

John Baer Spotify

Josh Baer

Machine Learning Platform Product Leader

When Good Models Go Bad: The Damage Caused by Wayward Models and How to Prevent it

Todd Underwood

Josh Baer

Engineering Director

Machine Learning is Going Real-Time: Are You Ready?

Stanford
Chip Huyen

Chip Huyen

Machine Learning Engineer at Snorkel AI, Adjunct Lecturer at Stanford

Cost Transparency and Model ROI at Intuit

Intuit
Ian Sebanja

Ian Sebanja

Machine Learning Platform

Srivathsan Canchi

Srivathsan Canchi

Head of Engineering, ML Platform Team

Driving Platform Adoption Success at Spotify

Spotify
James Kirk

James Kirk

Staff Machine Learning Engineer, Listening Experiences

Lex Beattie

Lex Beattie

Machine Learning Engagement Lead

Maisha Lopa

Maisha Lopa

Senior Product Manager, Machine Learning Platform

Sam N

Samuel Ngahane

Staff ML Software Engineer

Maya Hristakeva

Maya Hristakeva

Machine Learning Engineering Manager

PANEL

AI Operationalization: Where the AI Rubber
Hits the Road for the Enterprise

Conor Jensen
Moderator
Director of AI Consulting and Data Science
Dataiku
Sarah Cullem
Standard
Panelist
Director, Head of DTC Analytics & Data Science
Clorox
Rasool Tahmasbi
Standard
Panelist
Lead Data Scientist
Palo Alto Networks
Mike Beckert
Standard
Panelist
Data Scientist
The Janssen Pharmaceutical Companies of Johnson & Johnson

Get your Virtual TWIMLcon On Demand Pass today!
Order now starting at $499 $399

Exclusive: Level-Up as an AI/ML Leader With On-Demand Access to TWIMLcon's Half-Day Executive Summit

EXECUTIVE SUMMIT KEYNOTE
Fran Bell in Collared jacket outdoors

Franziska Bell

VP, Head of Data and Analytics

bp

Franziska Bell is vice president and head of data and analytics at bp. She is a career data professional and data science leader with experience in multiple industries and companies, including serving as the head of data science platforms at Uber. In this keynote interview, Franziska and Sam explore best practices for successfully launching and deploying ML & AI solutions for the enterprise and strategies for mitigating risks that lead to ML project failures.
Executive Summit Panels

Building the Business Case for ML Platforms

Divya Jain

Divya Jain

Director of ML Platform Adobe

Justin Norman

Justin Norman

Vice President Data Science & Analytics Yelp

Kirk Borne

Kirk Borne

Principal Data Scientist and Executive Advisor Booz Allen Hamilton

Why ML Projects Fail and How to Ensure Their Success

Andy Minteer

Andy Minteer

Senior Director, Digital Transformation - Head AI Products Walmart

Adrien Cartier

Kirk Borne

VP of Data Science

jürgen-weichenberger

Jurgen Weichenberger

Data Science Senior Principal & Global AI Lead, Resources Assenture

Building Teams and Culture that Support ML Innovation

Ziad Ashgar

Ziad Asghar

Vice President, Product Management Qualcomm

Pardis Noorzad

Pardis Noorzad

Noorzad, Head of Data Science Carbon Health

Ameen Kazerouni

Ameen Kazerouni

Chief Analytics Officer Orangetheory Fitness

Ameen Kazerouni
“Fantastic conversation on building teams and culture that support ML innovation, followed by an insightful round-table discussion.”
Ameen Kazerouni
Chief Analytics Officer Orangetheory fitness

Get your TWIMLcon On Demand
Executive Summit Pass today!

In Total, More than 50 Speakers
Joined TWIMLcon to Share their Lessons-Learned About How to Build and Scale Real-World ML and AI Systems and Products

Adrien Cartier
Executive Summit
VP of Data Science
Ocelot Consulting
Aman Khan Spotify
Standard
Product Manager
Spotify
Ameen Kazerouni
Executive Summit
Chief Analytics Officer
Orangetheory Fitness
Andy Minteer
Executive Summit
Senior Director, Digital Transformation - Head AI Products
Walmart Global Tech
Ariel Biller
Evangelist
ClearML
Chip Huyen
Standard
Machine Learning Engineer at Snorkel AI, Adjunct Lecturer at Stanford
Snorkel AI
Chris Albon
Keynote
Director of Machine Learning
WikiMedia
Conor Jensen
Moderator
Director of AI Consulting and Data Science
Dataiku
Danielle Dean
Standard
Technical Director of Machine Learning
iRobot
David Hershey
Solutions Architect
Tecton
Diego Oppenheimer
Chief Executive Officer
Algorithmia
Divya Jain
Executive Summit
Director of ML Platform
Adobe
Dotan Asselmann
Co-Founder & CTO
theator
Faisal Siddiqi Netflix
Keynote
Director of Engineering, Personalization Infrastructure
Netflix
Fran Bell in Collared jacket outdoors
Executive Summit
Keynote
VP, Head of Data and Analytics
bp
Hussein Mehanna
Executive Summit
VP, Head of ML/AI
Cruise
Ian Sebanja
Standard
Product Manager, Machine Learning Platform
Intuit
Jurgen Weichenberger
Executive Summit
Data Science Senior Principal & Global AI Lead, Resources
Accenture
Jack Ploshnick
Standard
Customer Data Scientist
Splice Machine
James Fort
Standard
Senior Product Manager, Simulation and Computer Vision
Unity Technologies
James Kirk
Staff Machine Learning Engineer, Listening Experiences
Spotify
Jeff Fletcher
Cloud Machine Learning Specialist
Cloudera
Jennifer Prendki
Standard
Founder and CEO
Alectio
John Posada
Partner Solutions Architect
Dataiku
Jonathan Hogins
Standard
Senior Software Engineer
Unity Technologies
John Baer Spotify
Standard
Machine Learning Platform Product Lead
Spotify
Justin Norman
Standard
Vice President Data Science & Analytics
Yelp
Kathy Baxter
Principal Architect, Ethical AI Practice
Salesforce
Kirk Borne
Executive Summit
Principal Data Scientist and Executive Advisor
Booz Allen Hamilton
Krishna Gade
CEO and Founder
Fiddler
Kristopher Overholt
Solution Engineer
Algorithmia
Lex Beattie
Standard
Machine Learning Engagement Lead
Spotify
Maisha Lopa
Senior Product Manager, Machine Learning Platform
Spotify
Mathew Salvaris
Standard
Lead Principal Machine Learning Scientist
iRobot
Maya Hristakeva
Standard
Machine Learning Engineering Manager
Spotify
Mike Beckert
Standard
Panelist
Data Scientist
The Janssen Pharmaceutical Companies of Johnson & Johnson
Mike Del Balso
Standard
Co-Founder and CEO
Tecton
Mohamed Elegendy
Standard
VP of Engineering, AI Platform
Rakuten
Mohan Muppidi
ML Cloud Architect
iRobot
Monte Zweben
CEO
Splice Machine
Pardis Noorzad
Executive Summit
Head of Data Science
Carbon Health
Paul van der Boor headshot
Executive Summit
Senior Director of Data Science
Prosus Group
Priyank Patel
Standard
Machine Learning Product Manager
Cloudera
Rasool Tahmasbi
Standard
Panelist
Lead Data Scientist
Palo Alto Networks
Rob Harrell
Staff Product Manager
Fiddler
Romer Rosales
Standard
Head of Consumer AI
LinkedIn
Sam Charrington
Executive Summit
Standard
Moderator
Founder
TWIML
Sam N
Staff ML Software Engineer
Spotify
Sarah Bird
Responsible AI Leader, Azure Cognitive Services
Microsoft
Sarah Cullem
Standard
Panelist
Director, Head of DTC Analytics & Data Science
Clorox

Memorable Insights

“If you’re serious about your data, you want to invest in your platforms.”
Solmaz Shahalizadeh
VP of Commerce Intelligence, Shopify
Ameen Kazerouni
“The currency of an analytics team is trust, not data.”
Ameen Kazerouni
Chief Analytics Officer, Orangetheory Fitness
“It is our obligation to bring our customers on the journey with us. We need to be in the mindset that we are enabling people to do their jobs."
Jurgen Weichenberger
Data Science Senior Principal & Global AI Lead, Resources, Accenture
“Now it’s about productization and treating models less like a crystal chandelier and more like a disposable coffee cup. If you find a better one, use it and throw away the old one.”
Chris Albon
Director of Machine Learning at WikiMedia
“This is the greatest technology of our lifetime, now it’s about getting the tools to be able to do it at scale”
Diego Oppenheimer
CEO of Algorithmia
Justin Norman
“The goal is to produce an ML system that functions reliably and that can replicate that at scale.”
Justin Norman
VP Data Science & Analytics, Yelp

Watch it All at Your Convenience
Starting at Just $499 $399

ProFESSIONAL

On Demand

Includes

Video recordings of TWIMLcon sessions delivered by leading AI and Machine Learning users including Netflix, Shopify, LinkedIn, Spotify, Google, iRobot, Intuit, Yelp, Salesforce, Prosus Group, Palo Alto Networks, Microsoft, and more.

Limited time offer!

$499 $399

Executive

On Demand

Includes

Additional Executive Summit content featuring executives at bp, Adobe, Booz Allen, Walmart, Accenture, Orangetheory Fitness, Cruise, Prosus, Qualcomm, Yelp and more.

Limited time offer!

$999 $799

TWIMLcon 2019 Icon

BONUS Opportunity

Add TWIMLcon 2019 On Demand access to your order for only $199.
Includes: 27 sessions, 13+ hours of content, featuring practitioners and leaders from Airbnb, CapitalOne, Facebook, NVIDIA, Stripe, SurveyMonkey, Twitter, and many, many more.

Use the form below to complete your purchase and get immediate access to 20+ hours of TWIMLcon On Demand content

*Lead a team? Contact us for details about team purchase discounts.

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ABOUT TWIML

TWIMLcon: AI Platforms is brought to you by Sam Charrington and the team behind the TWIML AI Podcast.

The conference has its roots in a series of podcast interviews and ebooks on the topic of AI Platforms published going back to the fall of 2018. The series – which featured interviews with ML Platforms and Infrastructure engineers and leaders from Facebook, Airbnb, LinkedIn, OpenAI, Shell and Comcast – resonated strongly with listeners and remains one of our most popular series to this day.

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