Senior Applied Scientist, Agentic AI

🔥 3 minutes ago

🇺🇸 United States – Remote

💵 $164.4k - $262.6k / year

⏰ Full Time

🟠 Senior

🧬 Research Scientist

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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

• Own ambiguous applied-science problems end to end, from identifying opportunities and forming hypotheses through data analysis, modeling, experimentation and production iteration • Develop and compare machine learning and LLM-based approaches to improve customer experiences • Establish useful baselines, adapt relevant research and add complexity when supported by evidence • Build reliable datasets and offline evaluations • Design online experiments connecting model quality to meaningful customer and business outcomes • Partner with engineering, product, design and science teams to turn methods into reliable production capabilities • Balance quality, safety, latency and cost • Write maintainable Python and SQL • Contribute production-ready scientific components • Share methods, findings and technical decisions with scientists and engineers

🎯 Requirements

• 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 • Depth in recommendations, ranking, search, personalization or conversational AI • Experience with large-scale datasets, experimentation or A/B testing, and model-performance measurement • Understanding of data quality, bias, uncertainty and causal impact • Practical understanding of LLM-based systems, including context, generation, evaluation and limitations • Strong Python and SQL skills • Ability to develop tested, reusable, production-integrated code • Clear technical communication and track record of delivering with engineering, product and science partners • Experience with recommendation, ranking or personalization systems is nice-to-have • Deep hands-on experience building and evaluating LLM-based or agentic systems in production is nice-to-have • Experience with model distillation, supervised fine-tuning, preference optimization or small-model deployment is nice-to-have • Experience evaluating multi-turn conversations, recommendation sets, session quality or longer-horizon customer outcomes is nice-to-have • Familiarity with large consumer marketplaces, sparse and delayed outcomes, cold-start experiences, or real estate is nice-to-have • Research contributions adapting new methods to practical problems are nice-to-have

🏖️ Benefits

• Equity awards based on factors such as experience, performance and location • Remote work from a physical location of choice • Flexible distributed work through Cloud HQ • Equal employment opportunity and inclusive work environment

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