Software Engineer Pricing MLOps

About Opendoor

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.

The Pricing team is the engine behind Opendoor’s ability to price homes with speed scale and confidence. We build the core platform that turns data models and business logic into the prices that power our entire business. Our services and data infrastructure are mission-critical to pricing decisions and automation and they must be fast accurate and resilient—because even small improvements can drive major business impact.

We’re looking for a senior-level Software Engineer to join our Pricing & ML team leading the design and evolution of the platform and tooling that productionize the machine learning models behind our pricing engine. This role is ideal for an engineer who enjoys working close to data and models has meaningful experience with ML workflows and wants to shape technical direction as well as ship high-impact systems. Our models are pragmatic and straightforward—we prioritize value reliability and iteration speed over complex research systems.

In this role you’ll work side-by-side with backend software engineers data scientists ML engineers product managers and partner engineering and operations teams to turn prototypes and ideas into robust scalable and observable production systems. You’ll own high-impact initiatives end-to-end mentor other engineers and have significant influence over how our pricing platform evolves and how we shape the future of real estate.

• Lead the design and implementation of services tooling and workflows that enable reliable training deployment and monitoring of pricing and ML models
• Work closely with researchers and analysts to convert model prototypes into clean testable production-ready Python code and systems
• Own and operate model pipelines end-to-end — including data ingestion training validation versioning deployment and monitoring
• Design and maintain workflows that support the full ML lifecycle: experimentation training evaluation deployment and iteration
• Develop and optimize data access patterns and SQL queries over large complex datasets
• Implement robust automation for key ML lifecycle workflows (e.g. scheduled retraining rollbacks A/B tests canary releases)
• Drive improvements in reliability observability performance and cost-efficiency across ML pipelines and model-serving environments
• Proactively address real-world challenges like data drift model decay and changing market conditions in the real estate domain
• Contribute to and help define shared ML infrastructure patterns and best practices across the Pricing & ML team
• Lead code reviews and technical design discussions; mentor and support other engineers on ML-adjacent work
• Participate in and help improve on-call and incident response processes for ML systems

• 8+ years of experience in software engineering or 6 Years with a Masters or ML engineering including substantial work with ML-adjacent or production ML workflows
• Strong proficiency in Python with a track record of writing maintainable modular and well-tested production code
• Solid experience working with SQL (queries joins indexing and performance optimization)
• Proven experience owning and operating data pipelines and/or model training/serving pipelines in production or high-stakes environments
• Deep familiarity with the end-to-end ML lifecycle (training evaluation deployment monitoring and iteration)
• Demonstrated ability to make and communicate technical design decisions and tradeoffs across multiple stakeholders
• Strong collaboration and communication skills especially when working with data scientists researchers and cross-functional partners
• A bias toward impact learning and pragmatic solutions in a fast-moving high-stakes domain

Focus:

•  - ML infrastructure and operations rather than model research.
•  - Building deploying and maintaining ML pipelines and systems.
•  - All roles are expected to be hands-on coding roles.
•  - All MLOps roles are expected to be Seattle-based.

Nice to Have

• Experience working on ML systems in business-critical environments (e.g. pricing forecasting logistics marketplaces risk)
• Familiarity with ML ops concepts and tools (e.g. model serving frameworks feature stores experiment tracking 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 dashboards)
• Experience with streaming / event-driven systems (e.g. Kafka) or scheduling/orchestration tools
• Comfort working in a Linux-based cloud-hosted environment (e.g. AWS)
• Interest in real estate or other messy high-stakes domains with imperfect data

#LI-DM

What We Do

Founded in 2014 Opendoor’s mission is to empower everyone with the freedom to move. We believe the traditional real estate process is broken and confusing. It often comes with unexpected costs the added burden of coordinating multiple third parties and the uncertainty of a transaction falling through. Our goal is simple: build a digital end-to-end customer experience that makes buying and selling a home simple certain and fast. We have assembled a dedicated team with diverse backgrounds and talents across engineering operations design operations mortgage finance legal and more to deliver strong results. More than 85000 customers have selected us as a trusted partner in handling one of their largest financial transactions.

Why Work With Us

We’re on a mission to power life’s progress one move at a time

Gallery