Applied Scientist AI/ML

What you'll do

• Improve and deploy deep neural network home valuation models and interpretable models that explain pricing decisions.
• Use unstructured data such as images, videos, and text in forecasting and valuation pipelines.
• Improve production feature engineering, model training, human-in-the-loop pricing, and risk and optimization systems.

What they ask for

• Strong Python software engineering skills and experience contributing to production codebases.
• Experience developing and deploying ML models end-to-end, from research and prototyping through production implementation.
• Hands-on experience with deep learning architectures, including ConvNets, Transformers, or similar.
• Advanced degree (MS or PhD) in computer science, statistics, mathematics, or a related quantitative field; solid foundation in statistics and experimental design.

Nice to have

• Familiarity with Pyspark and distributed data processing; background in search, recommendation systems, or personalization.
• Experience with large language models (LLMs) or vision-language models (VLMs); interest in real estate.

Tools

Python, ConvNets, Transformers, Pyspark, LLMs, VLMs

AI focus

Apply machine learning and AI to home valuation, pricing explainability, multimodal forecasting, human-in-the-loop pricing, and risk and operational optimization.