About the role

As a Principal Applied Scientist, you will set the science direction for advanced reasoning and long-running agent systems within the Agentic AI organization. You will partner closely with applied scientists, machine learning engineers, software engineers, product leaders, and senior stakeholders to define the science roadmap for Zillow's agentic experiences. This is a high-impact principal individual contributor role responsible for translating emerging advances in agentic AI into reliable, differentiated customer experiences.

You will get to

• Define and drive the end-to-end applied science strategy for advanced reasoning and long-running agent systems, balancing innovation, customer value, reliability, safety, and business priorities.
• Advance agent capabilities through agent architecture and harness design, context and memory engineering, test time scaling, post-training, evaluation and data flywheel.
• Establish rigorous evaluation frameworks for agentic systems, including task- and trajectory-level evaluation, long-horizon benchmarks, controlled experiments, ablation studies, and online measurement.
• Influence senior and executive stakeholders by clearly communicating scientific insights, technical trade-offs, risks, and recommendations that shape Zillow's Agentic AI product and platform strategy.
• Stay at the forefront of research in agentic AI and foundation models, selectively introducing advances that materially improve Zillow's customer experiences.
• Represent Zillow's work through publications, conference presentations, open-source contributions, patents, and external technical engagement.

This role has been categorized as a Remote position. "Remote" employees do not have a permanent corporate office workplace and, instead, work from a physical location of their choice, which must be identified to the Company. U.S. employees may live in any of the 50 United States, with limited exceptions.

In California, Connecticut, Maryland, Massachusetts, New Jersey, New York, Washington state, and Washington DC the standard base pay range for this role is $191,300.00 - $305,700.00 annually. This base pay range is specific to these locations and may not be applicable to other locations.In Colorado, Hawaii, Illinois, Maine, Minnesota, Nevada, Ohio, Rhode Island, Vermont, and Virginia the standard base pay range for this role is $181,800.00 - $290,400.00 annually. The base pay range is specific to these locations and may not be applicable to other locations.

In addition to a competitive base salary this position is also eligible for equity awards based on factors such as experience, performance and location. Actual amounts will vary depending on experience, performance and location. Employees in this role will not be paid below the salary threshold for exempt employees in the state where they reside.

Who you are

• You have a PhD degree in Computer Science, Machine Learning, Statistics, Mathematics, or a related field, or equivalent experience demonstrating comparable depth of technical expertise, scientific leadership, and impact in production AI systems
• 8+ years of industry experience building and deploying large-scale, high-impact AI systems.
• You have deep expertise in large language models and agentic AI, with experience turning research ideas into reliable customer-facing systems.
• Experience developing AI agents with capabilities such as multi-step reasoning, long-running execution, and proactive behavior.
• Extensive hands-on experience across agent architecture and harness design, context and memory engineering, test-time scaling, and post-training.
• Extensive experience establishing rigorous evaluation frameworks for complex AI systems, including benchmark design, experimentation, measurement of reliability and end-to-end impact
• You have a proven track record of leading complex, ambiguous, cross-functional initiatives from scientific framing and prototyping through production deployment, monitoring, and measurable customer or business impact.
• Demonstrated technical leadership, mentorship, and ability to influence across science, engineering, product, and executive audiences.
• You demonstrate science leadership through high-impact production systems, patents, publications, open-source contributions, conference presentations, or equivalent industry impact.