About

Hi, I’m Riccardo Parola — most people online know me as Pappol.

I work as an Associate AI & Data Engineer at PwC in Trento, Italy, where I spend my time building the systems that sit between raw data and useful intelligence: data pipelines, retrieval and machine learning components, and the unglamorous infrastructure that decides whether any of it actually works in production.

My background is split across the two halves of that job. I hold a BSc in Computer Science, which gave me the engineering foundations, and an MSc in Artificial Intelligence, which gave me the modeling side and a healthy respect for how differently theory and production behave. The space between those two worlds is more or less where I’ve chosen to live.

What I care about, in roughly this order: AI engineering (turning models into things people can rely on), data pipelines (the part that quietly determines everything downstream), and machine learning in production (monitoring, drift, evaluation, and all the realities that lecture slides skip). I’m drawn to the boring-but-load-bearing layers of a system, because they’re usually the ones that make or break it.

This blog is where I write down the lessons I’d otherwise have to relearn — practical notes, the occasional reflection, and whatever I’ve recently broken and fixed. I try to keep it concrete and honest, with fewer hot takes and more “here’s what actually happened.”

If you want to talk shop, disagree with something I wrote, or just say hello, I’m happy to hear from you.