Software Engineer, ML Pricing

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August 26

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Opendoor

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Real Estate • Marketplace

Opendoor is a company that simplifies the process of buying and selling homes. Through their platform, homeowners can quickly receive a cash offer and sell their home without the hassle of showings and staging. Opendoor aims to make moving easier by providing a fair price and a seamless selling experience. The company serves a large number of customers, with a new homeowner requesting an offer every 60 seconds. Additionally, Opendoor offers home insights and tools to assist sellers. They work with builders, agents, and vendors to provide a full-service real estate experience.

1001 - 5000 employees

Founded 2014

🏠 Real Estate

🏪 Marketplace

📋 Description

• At Opendoor, pricing is at the core; models influence real estate transactions across the country. • Work side-by-side with applied researchers and modelers to build and productionize machine learning pricing models. • Collaborate across the full ML lifecycle: experimentation, training, evaluation, deployment, monitoring, and iteration. • Convert prototypes into robust, production-grade code and own model pipelines end-to-end. • Contribute to shared ML infrastructure and tooling while focusing on business-critical problems. • Support day-to-day pricing model operations and address retraining, data drift, and model decay. • Navigate real estate-specific ML challenges: heterogeneous data, complex seasonality, sparse regions, and high financial stakes. • Drive engineering best practices within the ML codebase: maintainable, testable, scalable systems.

🎯 Requirements

• 2–4 years of experience in software engineering, ideally with exposure to machine learning workflows. • Enjoys working closely with data scientists and researchers and has strong collaboration and communication skills. • Comfortable navigating data pipelines, model training pipelines, and production environments. • Fluent in writing maintainable, modular, and testable Python code. • Motivated by impact and learning — not just building infrastructure for others. • Bonus: Experience working on ML systems in business-critical environments (pricing, forecasting, logistics). • Bonus: Familiarity with MLflow, Airflow, Delta Lake, or Spark. • Bonus: Interest in real estate or other messy, high-stakes domains with imperfect data. • Bonus: Experience monitoring model performance in production (e.g., drift detection, quality alerts).

🏖️ Benefits

• $143,200-$179,000 base pay annually, plus RSUs and bonuses • Unlimited PTO • Medical/dental/vision insurance • Life insurance • 401(k) to eligible employees