Building an ML Platform: Insights, Community, and Advocacy // Stephen Batifol // #178
Episode description
MLOps Coffee Sessions #178 with Stephen Batifol, Building an ML Platform: Insights, Community, and Advocacy.
// Abstract
Discover how Wolt onboards data scientists onto the platform and builds a thriving internal community of users. Stephen's firsthand experiences shed light on the importance of developer relations and how they contribute to making data scientists' lives easier. From top-notch documentation to getting-started guides and tutorials, the internal platform at Wolt prioritizes the needs of its users.
// Bio
From Android developer to Data Scientist to Machine Learning Engineer, Stephen has a wealth of software engineering experience at Wolt. He believes that machine learning has a lot to learn from software engineering best practices and spends his time making ML deployments simple for other engineers. Stephen is also a founding member and organizer of the MLOps.community Meetups in Berlin.
// MLOps Jobs board
// MLOps Swag/Merch
https://mlops-community.myshopify.com/
// Related Links
--------------- ✌️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 Stephen on LinkedIn: https://www.linkedin.com/in/stephen-batifol/
Timestamps:
[00:00] Stephen's preferred coffee
[00:32] Takeaways
[01:35] Please like, share, and subscribe to our MLOps channels!
[03:00] Creating his own team!
[04:44] DevRel
[06:32] The door dash of Europe
[11:28] Data platform underneath
[12:55] Cellular core deployment uses open source
[14:21] Alibi
[16:08] Kafka
[16:59] Selling points to data scientists
[20:05] Language models concern data scientists
[22:12] Incorporating LLMs into the business
[23:55] Feedback from data scientists and end users
[27:37] User surveys
[30:11] Evangelizing and giving talks
[35:25] Tech Hub Culture in Berlin
[38:38] Kubernetes lifestyle
[42:55] Interacting with SREs
[45:28] Wrap up