Applied Scientist - ML/Ai

About the Role We’re looking for an Applied Scientist (ALL LEVELS) 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 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 $156,800-$310,000 annually, plus RSUs. 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. #LI-RO At Opendoor our mission is to tilt the world in favor of homeowners and those who aim to become one. Homeownership matters. It's how people build wealth, stability, and community. It's how families put down roots, how neighborhoods strengthen, how the future gets built. We're building the modern system of homeownership giving people the freedom to buy and sell on their own terms. We’ve built an end-to-end online experience that has already helped thousands of people and we’re just getting started.

Design and deploy architectural improvements to deep neural network-based home valuation models. Collaborate with cross-functional teams to integrate unstructured data into forecasting pipelines and enhance human-in-the-loop pricing systems.

Requires strong software engineering skills in Python and experience developing end-to-end machine learning models. An advanced degree (MS or PhD) in a quantitative field is required along with a solid foundation in statistics.

• Unlimited PTO • Medical insurance • Dental insurance • Vision insurance • Life insurance • 401(k) • Stock options

Relevées dans la description du poste. Confirmez les exigences importantes ci-dessus.

• Python
• Machine Learning
• Deep Learning
• Software Engineering
• Statistics
• Experimental Design
• Transformers
• ConvNets
• Pyspark
• Large Language Models
• Vision-Language Models
• Data Processing
• Recommendation Systems
• Feature Engineering
• Neural Networks

• Technology
• Data & Analytics
• Science & Research
• Software
• Engineering

Formation minimale

Maîtrise

Expérience minimale

2+ ans

Langue de l’offre

anglais

Heures de travail

40 heures par semaine