Applied Scientist AI/ML

What you'll do

• Design and deploy architectural improvements for deep neural network-based home valuation models.
• Build interpretable machine learning models to explain pricing decisions to customers.
• Integrate unstructured data like images, videos, and text into forecasting pipelines using LLMs and VLMs.
• Develop and implement end-to-end ML models from research and prototyping to production systems.
• Enhance feature engineering and model training pipelines for production environments.
• Improve risk and optimization models using real-world data and domain insights.
• Collaborate with Engineering and Operations teams to improve human-in-the-loop pricing systems.

What we're looking for

• Strong software engineering and coding skills in Python with experience contributing to production codebases.
• Experience developing and deploying ML models end-to-end from research and prototyping to 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.
• Strong communication and collaboration skills to convey technical ideas to cross-functional stakeholders.
• Familiarity with Pyspark and distributed data processing.
• Experience with large language models (LLMs), vision-language models (VLMs), search, or recommendation systems.