Applied Scientist

• 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 engineering and model training

• Experienced in designing, training, and analyzing machine learning models to solve real-world business problems, not just academic benchmarks
• Proficient in Python and familiar with common ML libraries (e.g., PyTorch, TensorFlow, CatBoost, scikit-learn, Hugging Face) and distributed data systems (e.g., Spark, Hive, Databricks, Airflow)
• Skilled in the scientific lifecycle: hypothesis formation, experiment design, result analysis, and clear communication to technical and non-technical partners
• Demonstrated experience in at least one of the following: search/information retrieval, personalized ranking/recommender systems, or generative AI/LLM-based systems
• Holds a PhD or Master’s degree in a relevant field (Computer Science, AI, Data Science, or related), or equivalent industry experience (typically 3-4+ years with a Master’s, or 1+ year with a PhD)
• Comfortable working near production systems and collaborating closely with engineers and cross-functional partners
• Brings curiosity and excitement for applying generative AI and LLMs to transform the home-shopping experience
• Approaches challenges with ownership, scientific rigor, and a growth mindset

equity awards