Applied Scientist, New Construction

About the team The Shopping AI team is at the heart of Zillow Group’s mission to create a seamless digital real estate marketplace. We build and own the machine learning systems that power Zillow ’s core user experiences—like personalized search, recommendations, and display optimization—across our apps and websites. Our close-knit group of engineers and scientists collaborates with product and design to apply the latest AI advancements, tackling large-scale challenges and shaping the future of home shopping at Zillow . About the role As an Applied Scientist, you will help drive the next generation of ranking, recommendation, and generative AI systems for Zillow ’s home-shopping experience. Your work will directly impact how millions of users discover and shop for homes, as you research, design, and deploy innovative machine learning models that power key product features. You’ll collaborate across disciplines to deliver solutions that make home shopping more intuitive, personalized, and efficient. You Will Get To Research, design, and prototype new machine learning models for Zillow ’s consumer products, including search, ranking, recommendations, and notifications. Lead the full model lifecycle: from ideation and offline experimentation on large datasets to online deployment, A/B testing, and ongoing performance monitoring. Develop and test novel modeling approaches, such as deep learning architectures and large language models (LLMs), to improve the home-shopping experience. Apply cutting-edge AI techniques, including LLM-based retrieval and RAG-style systems, to create more natural and conversational property search experiences. Optimize how and when homes are displayed to users, ensuring relevance and context in every interaction. Collaborate with engineers, product managers, and designers to define, execute, and iterate on impactful projects. Partner with data engineering and infrastructure teams to leverage large-scale distributed data systems for feature eng