Senior Applied Scientist, Agentic AI

Zillow

. Own ambiguous applied-science problems end to end, from identifying opportunities and forming hypotheses through data analysis, modeling, experimentation and production iteration .

Posted 11/10/2026full-timeRemote • United StatesSenior💰 $164,400 - $262,600 per yearWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates expertise in applied machine learning and statistical modeling, with a strong foundation in Python and SQL for developing production-ready solutions. Capable of collaborating effectively with cross-functional teams to enhance customer experiences through data-driven methodologies.

Highest-signal resume keywords

Applied Machine LearningStatistical ModelingPython ProgrammingSQL ProficiencyLarge-Scale Dataset Evaluation

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

Machine LearningStatistical FoundationsData AnalysisModel Performance MeasurementA/B TestingLLM-Based SystemsProduction DeliveryModel DistillationSupervised Fine-TuningPreference Optimization

Soft Skills

Clear Technical CommunicationCollaboration

Certifications & Qualifications

Bachelor’s Degree in Computer ScienceBachelor’s Degree in StatisticsBachelor’s Degree in MathematicsBachelor’s Degree in Electrical Engineering

Industry Keywords

RecommendationsRankingPersonalizationConversational AIData QualityBiasCausal ImpactConsumer MarketplacesCold-Start ExperiencesResearch Contributions

Tech Stack

Tools & technologies

PythonSQL

About the role

Key responsibilities & impact

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

What you’ll need

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

Comp & perks

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