Senior Machine Learning Engineer, Rich Media Experiences

Job not on LinkedIn

🕒 May 14

🏄 California, Connecticut, +6 more states – Remote

🏄 California – Remote 🦌 Connecticut – Remote 🏛️ District of Columbia – Remote 🏖️ New Jersey – Remote 🗽 New York – Remote 🦀 Maryland – Remote 🍂 Massachusetts – Remote ☕ Washington – Remote

💵 $171.7k - $274.3k / year

⏰ Full Time

🟠 Senior

🤖 Machine Learning Engineer

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Zillow

WebsiteLinkedInAll Job Openings

5001 - 10000 employees

Founded 2006

🏠 Real Estate

🛍️ eCommerce

👥 B2C

💰 $4.1M Post-IPO Equity on 2012-12

Real Estate • eCommerce • B2C

Zillow is a leading real estate and property rental marketplace that provides comprehensive information on homes, apartments, and properties for sale or rent. It offers users tools to search for properties, calculate mortgage rates, and connect with real estate agents. The platform also features innovative algorithms that provide Zestimates, which are estimated market values of homes. Zillow is a go-to resource for individuals looking to buy, sell, or rent properties, as well as for agents and brokers who want to reach a wider audience.

📋 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