Applied Scientist, New Construction - Remote

Overview

The Applied Scientist will contribute to Zillow Group’s mission by developing machine learning systems that enhance the home-shopping experience for millions of users.

In Short

• Research and design new machine learning models for Zillow's consumer products.
• Lead the full model lifecycle from ideation to online deployment.
• Develop and test novel modeling approaches including deep learning architectures.
• Optimize user interactions by enhancing property display relevance.
• Collaborate with cross-functional teams including engineers and product managers.
• Utilize large-scale distributed data systems for feature engineering.
• Apply cutting-edge AI techniques to improve search experiences.
• Foster an innovative, inclusive, and engaging work culture.
• Contribute to a recognized best workplace environment.
• Support the mission of creating a seamless digital real estate marketplace.

Requirements

• Experience in designing and analyzing machine learning models.
• Proficiency in Python and ML libraries like PyTorch and TensorFlow.
• Experience in search/information retrieval or recommender systems.
• PhD or Master’s degree in a relevant field or equivalent experience.
• Ability to work near production systems and collaborate closely with teams.
• Curiosity for applying generative AI and LLMs to real-world challenges.
• Strong communication skills for technical and non-technical audiences.
• Ownership and scientific rigor in approaching challenges.
• Commitment to fostering an inclusive work environment.
• Willingness to consider applicants with non-traditional backgrounds.

Benefits

• Competitive base salary with equity awards.
• Flexible work environment with a distributed-first model.
• Recognition as one of the best workplaces in the country.
• Opportunities for professional growth and innovation.
• Supportive and inclusive company culture.
• Involvement in reshaping the real estate industry.
• Access to a large user base to impact home shopping experiences.
• Collaboration with a close-knit team of engineers and scientists.
• Engagement with cutting-edge technology and AI advancements.
• Commitment to equal employment opportunity.