Zillow-posted 4 months ago
$134,000 - $214,000/Yr
Mid Level
251-500 employees

The Artificial Intelligence organization delivers unique AI-powered experiences to millions of customers. Within this organization, the Mortgage Operations AI team leads efforts to streamline the loan production process to enable a fully digital financing experience and provide consistent, unbiased, and personalized loan recommendations. This work aims to make the home-buying process less daunting and more manageable, while helping Zillow scale its mortgage business. We are empowering Loan Officers to build strong relationships with buyers by offering the best loan products for their needs. As an Applied Scientist on the MOAI team, you will focus on developing Agentic AI and Generative AI solutions that can reason, plan, and interact with data and tools to streamline mortgage operations. You’ll bring together LLM-based methods with classical ML models to design robust, trustworthy systems that improve how borrowers and Loan Officers experience the financing process. Your success will be measured by your ability to break down complex problems, experiment quickly, and deliver science-driven solutions that have real impact on customers and the business.

  • Develop agentic workflows.
  • Build intelligent agents that use LLMs, planning, and tool integration to support Loan Officers and improve borrower experiences.
  • Rapidly design and test solutions with offline evaluations and online experiments, and ship the winning approaches.
  • Combine generative reasoning with classical ML for end-to-end decisioning.
  • Track advances in GenAI and ML, bring relevant techniques into practice, and share insights across the org.
  • Clearly explain findings and trade-offs to scientists, engineers, and business partners to drive alignment.
  • 3+ years building and assisting in the production of AI/ML systems in Python with frameworks such as PyTorch, TensorFlow, or Scikit-learn.
  • Familiar with LLMs, multi-agent systems, tool-augmented reasoning, or other GenAI methods; excited to apply them in production.
  • Comfortable with predictive modeling and data-driven experimentation when reliability and scale are key.
  • Experienced with SQL and distributed tooling (Spark, Hive, Databricks) for large-scale, messy data.
  • Strong coding practices, including Git, CI/CD, testing, and code reviews.
  • Able to translate technical depth for varied audiences and build trust across disciplines.
  • Comprehensive medical, dental, vision, life, and disability coverages.
  • Parental leave and family benefits.
  • Retirement contributions.
  • Paid time off.
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