Building an ML Platform: Insights, Community, and Advocacy // Stephen Batifol // #178

MLOps Coffee Sessions #178 with Stephen Batifol, Building an ML Platform: Insights, Community, and Advocacy.// AbstractDiscover 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.// BioFrom 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 jobs.mlops.community// MLOps Swag/Merchhttps://mlops-community.myshopify.com/// Related Links⁠--------------- ✌️Connect With Us ✌️ -------------Join our Slack community: https://go.mlops.community/slackFollow us on Twitter: @mlopscommunitySign up for the next meetup: https://go.mlops.community/registerCatch 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