Senior Machine Learning Engineer, Rich Media 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.

Responsibilities

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

Requirements

Significant professional experience building and shipping machine learning models or ML-powered systems in production; Strong hands-on proficiency in Python and at least one modern machine learning framework, such as PyTorch or TensorFlow; Experience building and operating end-to-end machine learning workflows, including data pipelines, model training, evaluation, deployment, and monitoring; Strong foundation in machine learning fundamentals such as representation learning, structured prediction, computer vision, optimization, and failure analysis; Comfortable debugging model and system behavior in real-world environments and using metrics, logs, and experiments to improve outcomes; Collaborates effectively with applied scientists, software engineers, and product partners in ambiguous, cross-functional settings; Strong engineering judgment and ability to balance experimentation with reliability, speed, and long-term maintainability; Ability to communicate technical ideas clearly and influence decisions across disciplines

Nice to have

Experience in computer vision; spatial data; 3D; AR/VR; mapping; search; recommendation systems; related domains

Benefits

Equity awards based on factors such as experience, performance and location