A Playground for AI/ML Engineers

A Playground for AI/ML Engineers

Author: Demetrios January 23, 2026 Duration: 54:41

Paulo Vasconcellos is the Principal Data Scientist for Generative AI Products at Hotmart, working on AI-powered creator and learning experiences, including intelligent tutoring, content automation, and multilingual localization at scale.

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// Abstract

“Agent as a product” sounds like hype, until Hotmart turns creators’ content into AI businesses that actually work.


// Bio

Paulo Vasconcellos is the Principal Data Scientist for Generative AI Products at Hotmart, where he leads efforts in applied AI, machine learning, and generative technologies to power intelligent experiences for creators and learners. He holds an MSc in Computer Science with a focus on artificial intelligence and is also a co-founder of Data Hackers, a prominent data science and AI community in Brazil. Paulo regularly speaks and publishes on topics spanning data science, ML infrastructure, and AI innovation.


// Related LinksWebsite: paulovasconcellos.com.br

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Timestamps:

[00:00] Hotmart Data Science Challenges

[02:38] LLMs vs spaCy

[11:38] Use Cases in Production

[19:04] Coding Agents Virtual Conference Announcement!

[29:27] ML to AI Product Shift

[34:49] Tool-Augmented Agent Approach

[38:28] MLOps GPU Guide

[41:24] AI Use Cases at Hotmart

[49:34] Agent Tool Access Explained

[51:04] MLOps Community Gratitude

[53:22] Wrap up


Hosted by Demetrios, MLOps.community is a space for honest, meandering talks about the real work of making artificial intelligence systems actually work. This isn't about hype or theoretical papers; it's about the messy, practical, and often surprising journey of taking models from a notebook into a live environment. You'll hear from engineers and practitioners who are in the trenches, discussing the tools, the frustrations, and the occasional breakthroughs that define the day-to-day. The conversations are deliberately relaxed, covering everything from traditional machine learning pipelines to the new world of large language models and even the intangible "vibes" of team culture and process. Each episode peels back a layer on what "production" really means, whether that involves deploying a predictive service, managing an agentic system, or maintaining reliability as everything scales. Tuning into this podcast feels like grabbing a coffee with colleagues who aren't afraid to dig into the technical nitty-gritty while keeping the tone conversational and accessible. It's for anyone who builds, manages, or is just curious about the operational backbone that allows AI to deliver value, offering a grounded perspective often missing from the broader conversation.
Author: Language: en-us Episodes: 100

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