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Buying a home isn’t a small decision. It’s often the largest financial choice someone will make. So what does it take to build AI that people can actually trust in that moment? Kelsey Juraschka, Principal Machine Learning Engineer at Zillow, shares how her team is designing AI systems that support users from search to keys in hand. We get into: • What it really means to test non-deterministic systems • How Zillow approaches agentic AI at scale • Why evaluation and trust are product requirements, not add-ons • How AI tools are changing the way engineering teams work • What kind of mindset actually helps you succeed in AI today If you're an engineer, product leader, or just curious about how AI works behind the scenes at scale, this one’s for you. Read more about Zillow: https://hackajob.com/company/zillow?h... Are you looking for a new role? Create your free profile on hackajob today: https://hackajob.com/talent/sign-up Chapters: 00:00 Kelsey's journey into tech and machine learning 04:19 Role and responsibilities at Zillow 06:57 Building trust in AI for major life decisions 10:26 Zillow's history with AI and machine learning 14:25 Challenges in designing scalable AI systems 18:44 Impact of AI tools on collaboration and productivity 22:35 Building trust and collaboration in remote work 26:31 Future of Zillow and the housing journey 28:53 Skills and mindset for success in AI If you found this valuable, subscribe for more conversations with engineers building complex systems at scale.