Senior Applied Scientist, Agentic AI

About the team

The Agentic AI team at Zillow is at the forefront of transforming the real estate industry by helping millions of people use AI assistants to find their next home. Within this organization, the Agentic Solutions team develops AI-powered experiences that help people navigate their real estate journey, understand their options, make informed decisions and take action. Our applied scientists work closely with engineering, product and design to turn advances in AI into reliable features that deliver measurable customer value. Our work sits at the intersection of large language models and traditional machine learning, such as ranking and personalization, and we are a small team where every scientist has real ownership and influence over what we build.

About the role

As a Senior Applied Scientist on the Agentic AI team, you will tackle complex, ambiguous problems from scientific framing and modeling through evaluation, experimentation and production delivery, and help shape which problems we solve and how we measure success.

You will

• Own ambiguous applied-science problems end to end, from identifying an opportunity and forming a hypothesis through data analysis, modeling, experimentation and production iteration
• Develop and compare machine learning and LLM-based approaches to improve customer experiences, establishing useful baselines, adapting relevant research and adding complexity when the evidence supports it
• Build reliable datasets and offline evaluations, and design online experiments that connect model quality to meaningful customer and business outcomes
• Partner with engineering, product, design and science teams to turn promising methods into reliable production capabilities, balancing quality, safety, latency and cost
• Write maintainable Python and SQL, contribute production-ready scientific components, and share methods, findings and technical decisions with other scientists and engineers

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 $164,400.00 - $262,600.00 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 $156,200.00 - $249,400.00 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 are a hands-on applied scientist who enjoys turning new ideas into shipped features. You are curious, you learn new domains quickly, and you change direction when the results tell you to.

Must-haves

• Bachelor’s degree in Computer Science, Statistics, Mathematics, Electrical Engineering or a related quantitative field and 8+ years applying machine learning or advanced statistical modeling in industry, including production delivery; or an equivalent combination of education and experience
• Strong applied machine learning and statistical foundations, demonstrated through model development, evaluation and production impact
• Depth in a relevant area such as recommendations, ranking, search, personalization or conversational AI, with evidence of independently solving ambiguous problems and learning new domains
• Experience with large-scale datasets, experimentation or A/B testing, and model-performance measurement, including sound reasoning about data quality, bias, uncertainty and causal impact
• Practical understanding of LLM-based systems, including context, generation, evaluation and limitations, and the ability to apply that understanding to new problems
• Strong Python and SQL skills and the ability to turn an analysis or model into tested, reusable code that can be integrated into a production system

Clear technical communication and a track record of delivering with engineering, product and science partners, with personal ownership and sound tradeoffs

Nice-to-haves

• Experience with recommendation, ranking or personalization systems
• Deep hands-on experience building and evaluating LLM-based or agentic systems in production
• Experience with model distillation, supervised fine-tuning, preference optimization or small-model deployment, especially when balancing quality, latency and maintenance cost
• Experience evaluating multi-turn conversations, recommendation sets, session quality or longer-horizon customer outcomes
• Familiarity with large consumer marketplaces, sparse and delayed outcomes, cold-start experiences, or real estate
• Research contributions that show the ability to adapt new methods to a practical problem and establish whether they help

Get to know us

At Zillow, we’re reimagining how people move—through the real estate market and through their careers. As the most-visited real estate platform in the U.S., we help people navigate buying, selling, financing and renting with greater ease and confidence. Whether you're working in tech, sales, operations, or design, you’ll be part of a company reshaping an industry and helping more people make home a reality.

How we work is a key part of that transformation. Through Cloud HQ, our strategic approach to distributed work, most employees have the flexibility to work fr