Software Engineer - ML Ops - Pricing (Mid Level)

Software Engineer – ML Ops, Pricing

Seattle, WA

About the Team & Role

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 mid-level Software Engineer to join our Pricing & ML team, focused on building 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 and wants to deepen their exposure to ML workflows. 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 see your work move from design to deployment quickly, and you’ll have meaningful ownership over how our pricing platform evolves and how we shape the future of real estate.

What You’ll Do

• Work closely with researchers and analysts to convert model prototypes into clean, testable, production-ready Python code
• 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 datasets
• Implement tooling and automation for key ML lifecycle workflows (e.g., retraining, rollbacks, A/B testing, canary releases)
• Support day-to-day pricing model operations and address challenges like data drift, model decay, and changing market conditions
• Contribute to shared ML infrastructure and tooling while staying focused on solving business-critical pricing problems
• Help improve the reliability, observability, and performance of our ML pipelines and model-serving environments
• Participate in code reviews, technical discussions, and on-call/incident response related to ML systems

What You’ll Need

• 3+ years of experience in software engineering or ML engineering with exposure to ML workflows
• Strong proficiency in Python, with experience writing maintainable, modular, and testable code
• Experience working with SQL (queries, joins, indexing, and basic optimization)
• Comfort navigating data pipelines, model training pipelines, and production or near-production environments
• Familiarity with the end-to-end ML lifecycle (training, evaluation, deployment, monitoring)
• Strong collaboration and communication skills, especially when working with data scientists and researchers
• Motivation to learn, to work close to the ML lifecycle, and to deliver tangible business impact

Nice to Have

• Experience working on ML systems in business-critical environments (e.g., pricing, forecasting, logistics, marketplaces)
• Familiarity with ML ops concepts and tools (e.g., model serving frameworks, feature stores, experiment tracking)
• 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

Compensation

The base pay range for this position is $156,000-$215,000 annually, plus RSUs and bonuses. 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.

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