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MLOps@GetYourGuide // Jean Machado, Meghana Satish, Olivia Houghton, Theodore Meynard// #182

MLOps@GetYourGuide // Jean Machado, Meghana Satish, Olivia Houghton, Theodore Meynard// #182

FromMLOps.community


MLOps@GetYourGuide // Jean Machado, Meghana Satish, Olivia Houghton, Theodore Meynard// #182

FromMLOps.community

ratings:
Length:
64 minutes
Released:
Oct 20, 2023
Format:
Podcast episode

Description

MLOps podcast #182 with GetYourGuide's Jean Machado, DataScience Manager, Meghana Satish, MLOps Engineer, Olivia Houghton, Machine Learning Operations Engineer, Theodore Meynard, Data Science Manager, MLOps@GetYourGuide.

// Abstract
Join a team to talk about the journey of GYG with MLOps.

From the conception of their platform to the creation of the MLOps engineer role and to their current stack state.

// Bio
Jean Machado
Jean Carlo Machado is a DataScience Manager at GetYourGuide for the Growth Data Products team and the Machine Learning Platform Team. He is privileged to be able to work on turning ideas in data scinece from inception to production. Before GYG Jean was working in a startup in Brazil building its infrastructure from the ground up. Jean also likes community building and using technology for social good.

Meghana Satish
Meghana Satish is currently working as an MLOps Engineer at GetYourGuide. She has previously held positions at Amazon AWS in Berlin and Microsoft IT in Hyderabad. In addition to her career in technology, Meghana is also a talented singer, dancer, and yoga practitioner.

Olivia Houghton
Olivia has been working as an MLOps engineer at GetYourGuide for the past year and a half or so. Olivia's main work is in building and managing their activity ranking service.

Theodore Meynard
Theodore Meynard, Data Science Manager at GetYourGuide, leads the evolution of their ranking algorithm, enriching customer experiences. His hands-on journey from data scientist to leader has honed his expertise in MLOps and real-time ML. Beyond work, he's a co-organizer of PyData Berlin, underlining his commitment to community and collaborative learning.

// MLOps Jobs board
https://mlops.pallet.xyz/jobs

// MLOps Swag/Merch
https://mlops-community.myshopify.com/

// Related Links
Website: https://investing1012dot0.substack.com/
The Openness of AI report: https://research.contrary.com/reports/the-openness-of-ai

--------------- ✌️Connect With Us ✌️ -------------
Join our slack community: https://go.mlops.community/slack
Follow us on Twitter: @mlopscommunity
Sign up for the next meetup: https://go.mlops.community/register
Catch all episodes, blogs, newsletters, and more: https://mlops.community/

Connect with Demetrios on LinkedIn: https://www.linkedin.com/in/dpbrinkm/
Connect with Jean on LinkedIn: https://www.linkedin.com/in/jean-carlo-machado-53b15977/
Connect with Meghana on LinkedIn: https://www.linkedin.com/in/meghana-satish-2a825282/?originalSubdomain=de
Connect with Olivia on LinkedIn: https://www.linkedin.com/in/oliviaphoughton/
Connect with Theodore on LinkedIn: https://www.linkedin.com/in/theodore-meynard/

Timestamps:
[00:00] GetYourGuide team's preferred coffee
[00:55] Takeaways
[02:20] Shout out to Berlin MLOps Community
[02:38] Please like, share, and subscribe to our MLOps channels!
[03:39] The GetYourGuide platform
[05:45] GetYourGuide use cases
[11:51] Strong Leadership Vision
[13:59] Creating rituals
[16:55] Feedback on the loop for improvements
[18:35] Different components of GetYourGuide's ML Platform
[21:04] V2 service templates
[24:26] Biggest pain points
[27:02] Feature flags
[30:51] Data foundation
[36:25] Data Testing
[39:53] Cross-team Tool Adoption Process
[44:59] Regrets about design decisions made in the past
[47:53] What's next for the platform with LLMs?
[52:49] Non-data scientists suggesting use cases, language flexibility
[55:14] DevSecOps team's AI study group ideation
[59:25] Experiments in growth data products, marketing split
[1:01:47] Shout out to the Berlin MLOps Community!
[1:03:31] Wrap up
Released:
Oct 20, 2023
Format:
Podcast episode

Titles in the series (100)

Weekly talks and fireside chats about everything that has to do with the new space emerging around DevOps for Machine Learning aka MLOps aka Machine Learning Operations.