Zillow
Consumer · Real estate marketplace
Zillow has 38 active AI-related job listings. The majority of these roles, 66%, are focused on agents. Engineering is the dominant function, with 26 roles. Frequent tech tags include agent_orchestration, evals, and model_serving, suggesting a focus on deploying and managing AI agents. In the last 30 days, Zillow posted 16 new AI roles, representing a 220% increase compared to the previous 30-day period.
Currently tracking 28 active AI roles, down 34% versus the prior 4 weeks. Primary focus: Agent · Engineering. Salary range $104k–$432k (avg $205k).
Consumer · Real estate marketplace
Zillow currently has 34 active AI-related roles in our index. The most common open titles are: Principal Machine Learning Engineer, Agentic AI (2), Senior Data Scientist (2), Senior Machine Learning Engineer (2), Applied Scientist, Forecasting, Applied Scientist, New Construction. Most positions are in Engineering and Product.
Zillow's active AI hiring is concentrated in: agents (65%), application (24%), serving infrastructure (6%). These categories follow a seven-stage AI lifecycle: data, pre-training, post-training, serving infrastructure, agents, evaluation, and application.
Zillow is hiring AI talent in: United States (26 roles), Mexico (6 roles), India (1 role), Germany (1 role).
Job postings at Zillow most frequently reference: agent orchestration, model serving, llm observability, evals, tool use.
In the past 30 days, Zillow has posted 6 new AI-related roles. That is a -65% change versus the prior 30 days (17 → 6).
| Title | Stage | AI score |
|---|---|---|
| Applied Scientist, Forecasting Applied Scientist role focused on designing, evaluating, and deploying statistical, econometric, and machine learning methods for forecasting problems within Zillow. The role involves the end-to-end modeling lifecycle, from data engineering and feature creation to model deployment, monitoring, and explainability, with a strong emphasis on translating forecasts into actionable business insights and recommendations for senior leadership. Collaboration with cross-functional teams and improvement of shared forecasting tools and data pipelines are also key responsibilities. | Ship | 7 |