Applied Scientist AI/ML

Summary

Opendoor is on a mission to empower homeowners and those aspiring to become homeowners. They are seeking an Applied Scientist to advance applied machine learning and AI, focusing on improving valuation systems and tackling various ML challenges to enhance decision-making for customers.

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
• We’re a small, nimble team — there’s ample opportunity to work across the entire research and modeling stack

Skills

• 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 implementation in production systems
• 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 — you're comfortable working with cross-functional stakeholders and can communicate technical ideas clearly
• 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)
• A genuine interest in real estate — no prior experience required, but you'll engage deeply with housing data

Qualifications

Must Haves

• 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 implementation in production systems
• 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 — you're comfortable working with cross-functional stakeholders and can communicate technical ideas clearly

Nice to Haves

• 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)
• A genuine interest in real estate — no prior experience required, but you'll engage deeply with housing data

Benefits

• RSUs
• Unlimited PTO
• Medical/dental/vision insurance
• Life insurance
• 401(k) to eligible employees