Senior Applied Scientist, Agentic AI

Role overview

Turn applied machine-learning and language-model research into reliable customer-facing capabilities for people navigating real estate decisions. You’ll own ambiguous scientific problems from opportunity framing and hypothesis formation through modeling, evaluation, experimentation, and production iteration, working closely with product, design, and engineering.

Responsibilities

- Identify opportunities, frame hypotheses, and carry applied-science work through analysis, modeling, experimentation, and production refinement. - Compare machine-learning and language-model approaches, establish baselines, and adapt research where evidence supports its use. - Build trustworthy datasets and offline evaluations, and design online experiments that connect model quality to customer and business outcomes. - Partner across science, engineering, product, and design to deliver production capabilities while balancing quality, safety, latency, and cost. - Write maintainable Python and SQL, contribute production-ready scientific components, and share methods and findings.

Requirements

- Bachelor’s degree in a quantitative field such as computer science, statistics, mathematics, or electrical engineering, plus at least eight years applying machine learning or advanced statistical modeling in industry and delivering production work; equivalent education and experience may qualify. - 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, including independently solving ambiguous problems. - Experience with large datasets, experimentation or A/B testing, and model-performance measurement. - Sound reasoning about data quality, bias, uncertainty, and causal impact. - Practical understanding of language-model systems, including context, generation, evaluation, and limitations.

Benefits and work setup

- Remote role for U.S.-based employees, with work location identified at hire and some location exceptions.