Machine Learning Engineer, Zillow Shopping AI

Role Overview

You will join Zillow’s Shopping AI team to design, build, and ship production machine learning models powering the Zillow home-shopping experience across the app, website, and notifications.

Responsibilities

• Design, build, and ship new production ML models for core product features (Zillow app, website, email/push).
• Re-architect home ranking and recommendation systems to support advanced neural networks and faster experimentation across user surfaces.
• Own the full model lifecycle:
  • Offline experimentation & prototyping with massive datasets
  • Online deployment
  • A/B testing and performance monitoring
• Apply deep learning and LLMs to improve personalization and user experiences.
• Develop AI components that optimize what homes are displayed and when they are recommended.
• Collaborate cross-functionally with engineers, applied scientists, product managers, and designers to deliver the team roadmap.
• Improve ML infrastructure, development standards, and shared tooling to raise engineering excellence.

Requirements (Must Have)

• 1–3 years experience developing applications in search, personalized ranking, or recommender systems.
• Experience developing and deploying ML models that scale to high-traffic, latency-sensitive customer-facing services (hundreds of millions of requests/day).
• Strong programming skills in Python or Java.
• Familiarity with ML libraries including PyTorch, TensorFlow, CatBoost, scikit-learn, and Hugging Face.
• Experience with large-scale distributed data processing systems such as Hive, Spark, Airflow, or Databricks.
• Experience owning end-to-end lifecycle from offline experimentation through online deployment, A/B testing, and monitoring.

Remote Policy

• Role is categorized as Remote: you work from a physical location of your choice (within the U.S.), with limited exceptions.