The Applied Science AQ/EQ (Action/Emotion Quotient) Foundation team at Zillow is at the forefront of advancing intelligent systems that empower millions of customers for their home shopping journey. Our mission is to build cutting-edge models and agentic workflows that can provide actionable recommendations and execute tasks on behalf of users during one of the most complex and high-stakes financial decisions of their lives. We leverage Zillow’s vast, unique and domain-specific datasets to design adaptive AI systems that integrate with expert workflows and reduce the stress of the home-buying journey. As a PhD Research Intern on the AQ/EQ Foundation team, you will conduct state-of-the-art research in foundational models and building agentic AI systems. You will focus on fine-tuning and reinforcement learning of large language models (LLMs), with an emphasis on customizing them for Zillow’s domain. You’ll also explore the design of automated, agentic workflows that allow intelligent systems to reason, plan, and act in ways that directly improve the home-buying experience. This role offers the opportunity to collaborate with applied scientists, engineers, and product leaders while pushing the boundaries of personalization and intelligent automation. You'll design training algorithms and therefore the improved agentic AI workflow will be shipped to various Zillow Agentic Skills to power the integrated Zillow Copilot experience, which is a rare opportunity to transform the real estate industry.