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Software Engineer - ML Pricing

Opendoor

$143,200 - $179,000
Aug 26, 2025
Remote, US
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Opendoor is looking for a Software Engineer to join their Pricing & ML team to build and productionize machine learning models that power their pricing engine, addressing high-stakes decisions in real estate transactions.

Requirements

  • Python
  • PyTorch, scikit-learn, MLflow
  • Databricks, Spark, Delta Lake, Airflow, AWS
  • Has 2–4 years of experience in software engineering, ideally with exposure to machine learning workflows.
  • Is comfortable navigating data pipelines, model training pipelines, and production environments.
  • Is fluent in writing maintainable, modular, and testable Python code.
  • Experience working on ML systems in business-critical environments (e.g., pricing, forecasting, logistics).
  • Familiarity with tools like MLflow, Airflow, Delta Lake, or Spark.
  • Experience monitoring model performance in production (e.g., drift detection, quality alerts).

Responsibilities

  • Work closely with researchers and analysts to assist the development of pricing models, and convert prototypes into robust, production-grade code.
  • Own and operate model pipelines end-to-end — including training, validation, versioning, deployment, and monitoring.
  • Contribute to shared ML infrastructure and tooling as needed, while staying focused on solving business-critical problems.
  • Support day-to-day pricing model operations and address real-world ML lifecycle challenges like retraining, data drift, and model decay.
  • Navigate real estate-specific ML challenges (heterogeneous data, complex seasonality, sparse regions, high financial stakes).
  • Drive engineering best practices within the ML codebase — maintainable, testable, and scalable systems.

Other

  • Enjoys working closely with data scientists and researchers and has strong collaboration and communication skills.
  • Is motivated by impact and learning — not just building infrastructure for others.
  • An interest in real estate or other messy, high-stakes domains with imperfect data.