Job Description:

• 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 using metrics, logs, and experiments to improve outcomes
• collaborate effectively with applied scientists, software engineers, and product partners in ambiguous, cross-functional settings
• strong engineering judgment and know how to balance experimentation with reliability, speed, and long-term maintainability
• 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

Benefits:

• equity awards based on factors such as experience, performance, and location