Opendoor is looking for an experienced Research Scientist to improve their valuation systems by pushing the boundaries of applied machine learning and AI. The role will address challenging ML problems, including multi-modal modeling and operational optimization, to enhance decision-making using structured and unstructured data.
Requirements
- Strong software engineering and coding skills in Python, with experience contributing to production codebases
- 5+ years of experience developing and deploying ML models end-to-end — from research and prototyping to implementation in production systems
- Hands-on experience with deep learning architectures, including ConvNets, Transformers, or similar
- Solid foundation in statistics and experimental design
- Familiarity with Pyspark and distributed data processing
- Background in search, recommendation systems, or personalization
- Experience working with large language models (LLMs) or vision-language models (VLMs)
Responsibilities
- Design and deploy architectural improvements to our deep neural network (DNN)-based home valuation models
- Build interpretable ML models that can help us explain pricing decisions to customers
- Incorporate unstructured data — like images, videos, or text — into our forecasting and valuation pipelines using cutting-edge AI models (LLMs, VLMs, etc.)
- Collaborate with Engineering and Ops to enhance our human-in-the-loop pricing systems
- Improve the feature engineering and model training pipelines that power our production systems
- Rethink our risk and optimization models using real-world data and domain insight
Other
- Strong communication and collaboration skills — you’re comfortable working with cross-functional stakeholders and can communicate technical ideas clearly
- A genuine interest in real estate — no prior experience required, but you'll engage deeply with housing data
