Zillow logo
Zillow

Zillow is a leading online real estate marketplace covering the whole spectrum of purchasing, owning, and selling a home. In support of flexible work options and work-life balance,

Senior Machine Learning Engineer, Rich Media Experiences

Location

California + 7 moreAll locations: California | Connecticut | District Of Columbia | New Jersey | New York | Maryland | Massachusetts | Washington

Posted

25 days ago

Salary

$171.7K - $274.3K / year

Seniority

Senior

Bachelor DegreeEnglishPythonPyTorchTensorflow

Job Description

Senior Machine Learning Engineer, Rich Media Experiences

Zillow

• 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

Job 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

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