Senior Manager - Machine Learning Engineering

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July 4

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Opendoor

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Real Estate • Marketplace

Opendoor is a company that simplifies the process of buying and selling homes. Through their platform, homeowners can quickly receive a cash offer and sell their home without the hassle of showings and staging. Opendoor aims to make moving easier by providing a fair price and a seamless selling experience. The company serves a large number of customers, with a new homeowner requesting an offer every 60 seconds. Additionally, Opendoor offers home insights and tools to assist sellers. They work with builders, agents, and vendors to provide a full-service real estate experience.

1001 - 5000 employees

Founded 2014

🏠 Real Estate

🏪 Marketplace

📋 Description

• Lead, mentor, and grow a team of 5–9 machine learning engineers. • Own the design, delivery, and optimization of ML systems that support high-stakes, revenue-critical business functions (e.g., pricing, risk, recommendations, tail-management). • Partner closely with Product, Data Science, Backend Services, and Infrastructure teams to define priorities, shape roadmaps, and ensure seamless integration of ML solutions. • Drive best practices in ML development, model monitoring, deployment, and lifecycle management. • Maintain a high technical bar and ensure consistent operational excellence across your team. • Contribute to the long-term technical vision for the unique ML infrastructure and systems required in real estate.

🎯 Requirements

• Proven leadership experience managing ML engineering teams, ideally in a fast-paced or high-growth environment. • 3+ years of people management experience, including hiring, coaching, and performance management. • 7+ years of industry experience in software engineering or machine learning, with significant experience deploying ML models into production. • Experience delivering business-critical ML systems that directly influence revenue or core customer experience. • Strong cross-functional communication skills with the ability to translate technical solutions into business outcomes. • Solid understanding of backend architecture fundamentals (e.g., APIs, microservices, data pipelines) and how ML integrates within these systems. • Deep knowledge of ML engineering practices, including model training, evaluation, versioning, monitoring, and retraining strategies.

🏖️ Benefits

• unlimited PTO • medical/dental/vision insurance • life insurance • 401(k)