Applied Scientist

About the Role

We’re looking for an experienced Applied Scientist to push the boundaries of applied machine learning and AI at Opendoor. While this role will have a significant impact on our valuation systems — ensuring we provide the most accurate and transparent pricing possible — the scope goes well beyond pricing. You’ll work across a range of challenging ML problems, from multi-modal modeling to operational optimization, helping us rethink how we use structured and unstructured data to make better decisions for our customers.

What You'll Need

• 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 

• 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 Have

• 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 

What You'll Do

• 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.

Compensation

The base pay range for this position is $176,800-243,100 annually, plus RSUs and bonuses. Pay within this range varies by work location and may also depend on your qualifications, job-related knowledge, skills, and experience. We also offer a comprehensive package of benefits including unlimited PTO, medical/dental/vision insurance, life insurance, and 401(k) to eligible employees.