Senior Machine Learning Engineer, Media

About the team

As a Senior Machine Learning Engineer within Zillow’s Rich Media Experiences team, you’ll join a group focused on helping people better understand homes through immersive, AI-powered experiences. The team works on turning photos, video, and spatial signals into structured representations that power customer-facing products used by millions of shoppers. Within Rich Media Experiences, the Instant Floor Plans team is building systems that transform sensor-rich mobile captures into accurate floor plans and 3D representations that feed Zillow’s rich‑media and listing experiences.

This is a high-impact senior individual contributor role for someone who loves operating at the intersection of modeling and systems. As a Senior Machine Learning Engineer, you’ll help shape how Zillow builds production-grade machine learning systems for rich media experiences, partnering across applied science and engineering to turn promising ideas into reliable, scalable product capabilities.

• Design, build, and operate production‑grade machine learning systems that move from early ideas and prototypes into reliable customer‑facing services.
• Lead end‑to‑end machine learning work spanning data, training, evaluation, deployment, observability, and iteration in production.
• Partner closely with applied scientists and software engineers across backend, web, and mobile to integrate modern machine learning techniques into Zillow experiences.
• Improve the quality, latency, reliability, and maintainability of machine learning workflows that support floor plan and rich media products.
• Drive technical decisions in ambiguous problem spaces, especially where structured inference, computer vision, spatial signals, or performance tradeoffs matter.
• Help establish shared patterns, tooling, and best practices that raise the bar for machine learning engineering across the team.
• Mentor peers through strong technical execution, code review, debugging discipline, and thoughtful communication across functions.

This role has been categorized as a remote position. Remote employees do not have a permanent corporate office workplace and instead work from a physical location of their choice, which must be identified to the Company. U.S. employees may live in any of the 50 United States, with limited exceptions. In California, Connecticut, Maryland, Massachusetts, New Jersey, New York, Washington state, and Washington DC the standard base pay range for this role is $ - $ annually.

In Colorado, Hawaii, Illinois, Minnesota, Nevada, Ohio, Rhode Island, and Vermont the standard base pay range is $ - $ annually. In addition to a competitive base salary this position is also eligible for equity awards based on factors such as experience, performance and location. Employees in this role will not be paid below the salary threshold for exempt employees in the state where they reside.

• You have significant professional experience building and shipping machine learning models or ML‑powered systems in production.
• You have strong hands‑on proficiency in Python and at least one modern machine learning framework, such as PyTorch or Tensor Flow.
• You have experience building and operating end‑to‑end machine learning workflows, including data pipelines, model training, evaluation, deployment, and monitoring.
• You have a strong foundation in machine learning fundamentals such as representation learning, structured prediction, computer vision, optimization, and failure analysis.
• You are comfortable debugging model and system behavior in real‑world environments and using metrics, logs, and experiments to improve outcomes.
• You collaborate effectively with applied scientists, software engineers, and product partners in ambiguous, cross‑functional settings.
• You have strong engineering judgment and know how to balance experimentation with reliability, speed, and long‑term maintainability.
• You communicate technical ideas clearly and can influence decisions across disciplines.
• Experience in computer vision, spatial data, 3D, AR/VR, mapping, search, recommendation systems, or related domains is a plus.

Here at Zillow, we value the…