Senior Manager - Machine Learning Engineering

We’re seeking a Senior Manager, Machine Learning Engineering to lead our high-impact Pricing & ML team focused on building and scaling the machine learning ecosystem at the heart of our industry-leading pricing engine. This role is ideal for a hands-on, strategic leader with a track record of managing ML engineers and delivering production-grade solutions that directly impact revenue. You’ll lead a team of 5-9 engineers, drive project execution, and collaborate cross-functionally with product and business leaders to launch and refine experiences on the critical path of our multi-billion dollar per annum deal flow.

• 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.
  

• 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.
  

• Experience working with cloud-based ML stacks (e.g., AWS, GCP, Azure ML).
  
• Familiarity with modern MLOps practices and tooling.
  
• Prior experience with experimentation frameworks and causal inference a plus.

The base pay range for this position is $236,800.00 - $325,600.00 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.