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# Principal Machine Learning Engineer

- **Company:** ZILLOW INC
- **Location:** Remote, OR, United States
- **Salary:** $245,000.0 - $320,000.0
- **Contract:** Permanent contract
- **Skills:** A/B Testing, Artificial Intelligence, Airflow, Amazon Web Services, Microsoft Azure, Cloud Computing, Continuous Integration, Machine Learning, Reinforcement Learning, Large Language Models, Deep Learning, Kubernetes, Data Management, Machine Learning Operations
- **Published:** September 24, 2026
- **Apply:** https://find.jobs/jobs-near-me/apply/ats-redirect/?id=2984033948-2

## About the Role

* Machine learning
 * Deep learning
 * Large language models (LLMs)
 * Reinforcement learning / agentic AIPython
 * ML infrastructure (Kubeflow, Airflow, or similar)
 * Cloud platforms (AWS, GCP, or Azure)
 * MLOps and CI/CD for MLData engineering with big data tools
 * Experimentation and A/B testing

## Description

Zillow is seeking a Principal Machine Learning Engineer to lead agentic AI systems that power our real estate marketplace. You will design, build, and deploy large-scale ML and LLM-based agents for search, recommendations, pricing, and customer experiences. Partner with data science, product, and engineering to define technical strategy, architecture, and best practices. Mentor engineers, drive experimentation, and ensure robust, reliable ML pipelines. Help shape Zillow's next generation of AI-driven products that transform how people find, rent, and buy homes in a collaborative, flexible, and inclusive culture., * Design and lead architecture for large-scale ML and agentic AI systems powering Zillow's marketplace.

 * Develop, deploy, and maintain production ML and LLM-based agents for search, recommendation, and pricing.
 * Collaborate with data science, product, and engineering to define AI strategy and translate business needs into technical solutions.
 * Establish best practices for MLOps, experimentation, and model governance for reliability and scalability.
 * Mentor and guide engineers, fostering a culture of learning, experimentation, and inclusive collaboration.
 * Analyze product performance, run A/B tests, and iterate on models to improve customer experience and business impact.


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