Non-traditional Career Paths in MLOps // Matthew Dombrowski // MLOps Podcast #144

MLOps Coffee Sessions #144 with Matthew Dombrowski, Non-traditional Career Paths in MLOps co-hosted by Mihail Eric. // Abstract Let's explore the different aspects of ML and data roles and the variety of responsibilities each role entails! This conversation emphasizes the need for understanding the unique insights each role provides and the similarities in responsibilities and soft skills that are required across different roles.    This episode also highlights the significance of stakeholder alignment in the context of working in big companies and the importance of navigating these complexities for a successful career in ML. // Bio Matt has performed a number of MLOps positions including Solutions Consultant, Solutions Architect, and Product Manager from startups to large organizations. In his current role, Matt builds tools to help social media influencers discover unique and exciting Amazon products to recommend to their audiences. // MLOps Jobs board   https://mlops.pallet.xyz/jobs // 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 Mihail on LinkedIn: https://www.linkedin.com/in/mihaileric/ Connect with Matt on LinkedIn: https://www.linkedin.com/in/matthewdombrowski/ Timestamps: [00:00] Matt's preferred coffee [00:28] Mihail's new creation [05:09] Introduction to Matthew Dombrowski [06:02] Takeaways [08:30] Pizza and coffee nerds [10:54] Data careers [13:35] Matt's progression through the ml sphere [20:10] Dealing with machine learning [23:20] Transition from deep technical implementer to PM role [27:42] Data is a product [29:30] From start-ups to big companies [32:41] Ambiguity of ML [36:17] Matt's daily routine [40:23] Social media influencers [42:07] Developer advocate [44:00] Stakeholder alignment [49:41] Non-traditional career paths military influence [54:11] Good ways to recommend people to get into ML [57:56] MLOps Meetups all over the world [59:00] Wrap up