Principal Applied Scientist – User Modeling

🔥 12 hours ago

🇺🇸 United States – Remote

💵 $185.8k - $312.4k / year

⏰ Full Time

🔴 Lead

🧬 Research Scientist

🦅 H1B Visa Sponsor

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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

• Build user world models that help agents understand each shopper’s journey, goals, and how actions affect outcomes • Own LLM post-training pipelines, including SFT, DPO, and reinforcement fine-tuning (RFT/GRPO), end-to-end on GPU infrastructure • Build and train multi-category reward models (PRMs) that emit scalar signals from contrastive preference pairs • Design on-policy and online assessment using LLM-as-a-Judge frameworks to score live agent trajectories • Translate offline evaluation rubrics into generalizable reward functions for arbitrary production traces • Drive complex, ambiguous work end-to-end in collaboration with product, engineering, science, platform, and data teams • Provide technical leadership and mentorship • Translate state-of-the-art AI research into production impact for Zillow’s home-shopping experiences

🎯 Requirements

• PhD in Computer Science, Statistics, Economics, Machine Learning, or a related quantitative field, with depth in reinforcement learning or causal inference • Hands-on experience modeling user behavior at scale using sequence models over event streams, sessions, or trajectories • Experience predicting user intent or long-term outcomes • Practical depth in causal inference, including propensity scoring, treatment-effect estimation, and off-policy evaluation, or reinforcement learning applied to real sequential decision problems • Ability to independently scope and solve ambiguous problems end-to-end • Ability to provide technical leadership to scientists and MLEs • Working proficiency in Python and ML frameworks such as PyTorch or TensorFlow • Ability to run experiments and read, review, and debug code • Background in economics or econometrics, such as demand modeling or consumer choice • Published work in RL, causal inference, survival analysis, or user modeling/simulation • Experience with generative sequence models or conditional language generation for behavioral/conversational simulation • Experience with rare-event modeling and probability calibration at scale • Familiarity with two-sided marketplaces, real estate, or long-horizon consumer journeys

🏖️ Benefits

• Equity awards based on factors such as experience, performance and location • Remote work from a physical location of choice within the eligible U.S. locations • Flexible work through Cloud HQ • Equal employment opportunity and accommodation support