Software Engineer, Pricing MLOps

Responsibilities

• Lead the design and implementation of services, tooling, and workflows for reliable training, deployment, and monitoring of pricing and ML models
• Convert model prototypes from researchers and analysts into clean, testable, production-ready Python code
• Own and operate end-to-end model pipelines, including data ingestion, training, validation, versioning, deployment, and monitoring
• Design and maintain workflows supporting the full ML lifecycle: experimentation, training, evaluation, deployment, and iteration
• Develop and optimize data access patterns and SQL queries over large, complex datasets
• Implement automation for key ML lifecycle workflows such as scheduled retraining, rollbacks, A/B tests, and canary releases
• Drive improvements in reliability, observability, performance, and cost-efficiency across ML pipelines and model-serving environments
• Mentor other engineers and lead technical design discussions and code reviews

Requirements

• 8+ years of experience in software engineering, or 6 years of experience with a Master's degree in ML engineering
• Strong proficiency in Python with a track record of writing maintainable, modular, and well-tested production code
• Solid experience working with SQL, including queries, joins, indexing, and performance optimization
• Proven experience owning and operating data pipelines or model training/serving pipelines in production environments
• Deep familiarity with the end-to-end ML lifecycle (training, evaluation, deployment, monitoring, and iteration)
• Demonstrated ability to communicate technical design decisions and tradeoffs to cross-functional stakeholders

Preferred Qualifications

• Experience working on ML systems in business-critical environments such as pricing, forecasting, or marketplaces
• Familiarity with MLOps tools and concepts (e.g., model serving frameworks, feature stores, experiment tracking, or model registries)
• Experience with tools such as MLflow, Airflow, Spark, or Delta Lake
• Experience monitoring model performance in production (e.g., drift detection, quality alerts, or dashboards)
• Experience with streaming/event-driven systems (e.g., Kafka) or cloud-hosted environments (e.g., AWS)

About the Company

Opendoor is building the modern system of homeownership, giving people the freedom to buy and sell homes on their own terms through an end-to-end online experience.