Manager - Machine Learning Engineering

Senior Manager, Machine Learning Engineering
Location: San Francisco, CA or Seattle, WA (Hybrid – 4 days onsite per week)

Opendoor's mission is to make buying and selling a home as easy as the click of a button. We’ve transformed a complex, stressful process into a simple and transparent experience through data science, pricing models, and operational excellence. Our teams are building the modern real estate platform that empowers homeowners and buyers nationwide.
We’re looking for a hands-on, strategic leader to drive our Pricing & Machine Learning team. This role is focused on building and scaling the machine learning ecosystem that powers our industry-leading pricing engine. You’ll lead a team of 5–9 engineers and collaborate closely with product and business leaders to deliver ML systems that directly influence Opendoor’s revenue, customer experience, and pricing accuracy.

Responsibilities

• Lead, mentor, and grow a high-performing team of ML engineers.
• Own the design, delivery, and optimization of ML systems supporting revenue-critical business functions (e.g., pricing, risk, recommendations).
• Partner with Product, Data Science, Backend Services, and Infrastructure teams to define priorities and integrate ML solutions into production.
• Drive best practices in ML development, deployment, and lifecycle management.
• Maintain a high technical bar and ensure consistent operational excellence across the team.
• Contribute to the long-term technical vision for Opendoor’s ML infrastructure and platforms.

Basic Qualifications

• 3+ years of people management experience leading ML engineering teams.
• 8+ years of experience in ML or software engineering, including production deployment.
• Proven success delivering ML systems that directly influence revenue or customer experience.
• Strong understanding of backend architecture fundamentals (APIs, microservices, data pipelines).
• Deep knowledge of ML engineering practices: training, evaluation, versioning, monitoring, retraining.
• Familiarity with cloud-based ML stacks (AWS, GCP, Azure) and modern ML Ops tooling.
• Excellent cross-functional communication and collaboration skills.

Preferred Qualifications

• Experience with experimentation frameworks and causal inference.
• Prior experience in pricing, financial modeling, or marketplace systems.
• Track record of influencing product and business strategy through ML innovation.

The base pay range for this position is $205,000 – $253,600 annually, plus RSUs and performance bonus. Pay within this range varies by location and depends on qualifications, skills, and experience.
We offer a comprehensive benefits package including: Unlimited PTO, Medical, dental, and vision insurance, Life insurance, 401(k) retirement plan.

JR 9080
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