Evan Estola - On recommendation systems going bad, hiring ML engineers, giving constructive feedback, filter bubbles and much more - #9

Evan Estola - On recommendation systems going bad, hiring ML engineers, giving constructive feedback, filter bubbles and much more - #9

Author: Ronak Nathani, Guang Yang April 23, 2021 Duration: 1:12:35

Evan Estola (https://twitter.com/estola) is a Director of Engineering at Flatiron Health where he's leading software engineering teams focused on building Machine Learning products. Throughout this episode, Evan shares various stories when recommendation systems didn't work as expected, like this one time when members saw mathematically worst recommendations for meetups near them. He also shares why Schenectady, NY pops up on some lists of most popular cities and the story behind the Wall Street Journal article titled 'Orbitz steers Mac users to pricier hotels'. We also discuss skills Evan looks for when hiring ML engineers, how to give constructive feedback, filter bubbles and much more.


Behind every line of code, there's a person with a story, and that's where Software Misadventures finds its pulse. Hosts Ronak Nathani and Guang Yang pull up a chair with engineers, founders, and investors, but the conversation rarely stays in the technical manual. Instead, it wanders into the human territory of career detours, hard-won insights, and those unpredictable stumbles that often teach the most. This podcast is built on the idea that the journey is just as important as the destination, especially in the fast-moving tech world. You'll hear guests recount the projects that went sideways, the decisions they'd rethink, and the moments of clarity that emerged from the chaos. It’s a refreshingly honest look at the industry, emphasizing that expertise isn't just about what you build, but what you learn when things don't go as planned. Tune in for conversations that are less about perfect solutions and more about the real, sometimes messy, process of creating with technology. Each episode offers a blend of professional wisdom and personal narrative, making it a compelling listen for anyone curious about the lives woven into our digital landscape.
Author: Language: English Episodes: 55

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