At Cotality, we are driven by a single mission—to make the property industry faster, smarter, and more people-centric. Cotality is the trusted source for property intelligence, with unmatched precision, depth, breadth, and insights across the entire ecosystem. Our talented team of 5,000 employees globally uses our network, scale, connectivity and technology to drive the largest asset class in the world. Join us as we work toward our vision of fueling a thriving global property ecosystem and a more resilient society.

Cotality is committed to cultivating a diverse and inclusive work culture that inspires innovation and bold thinking; it's a place where you can collaborate, feel valued, develop skills and directly impact the real estate economy. We know our people are our greatest asset. At Cotality, you can be yourself, lift people up and make an impact. By putting clients first and continuously innovating, we're working together to set the pace for unlocking new possibilities that better serve the property industry.

Job Description:

We are seeking a visionary Director of Machine Learning Engineering to lead a high-performing team of ML engineers and MLOps specialists. This leader will bridge the gap between data science and production, ensuring our proprietary Automated Valuation Models (AVMs) are scalable, performant, and reliable.

The ideal candidate is a seasoned people leader who thrives at the intersection of large-scale distributed systems and advanced statistical modeling, with a proven track record of shipping ML products within the Google Cloud Platform (GCP) ecosystem.

Key Responsibilities

Strategic Leadership: Mentor and scale a dual-discipline team of ML Engineers and Operations specialists, fostering a culture of technical excellence and rigorous engineering standards.
AVM Architecture: Direct the end-to-end lifecycle of custom Automated Valuation Models, from architectural design in GCP to production deployment and real-time inference.
MLOps Excellence: Drive the adoption of CI/CD for ML (CT - Continuous Training), ensuring robust model versioning, automated testing, and seamless deployment via Vertex AI or GKE.
Data Strategy & Lineage: Oversee the engineering of automated feature stores and data pipelines, ensuring high-fidelity datasets for training, validation, and backtesting.
Performance & Scalability: Partner with Data Science and Product teams to solve bottlenecks in model latency, throughput, and cost-efficiency.
Quality Assurance: Implement sophisticated monitoring frameworks to detect feature drift and model decay, ensuring the long-term accuracy of valuation outputs.
Stakeholder Management: Translate complex technical roadmaps into actionable business value for executive leadership and cross-functional partners.

Job Qualifications:

Strategic Leadership: 8+ years of experience in ML or Software Engineering, with at least 3+ years in a dedicated people management role. You have a proven track record of scaling high-output teams and mentoring Staff-level engineers in the analytics or machine learning space.
Advanced ML Architecture: Deep hands-on expertise in the full ML lifecycle—from research and algorithm development to feature engineering and distributed data processing. You don't just build models; you design the systems that make them reproducible and scalable.
GCP Ecosystem Mastery: Architect-level command of Google Cloud Platform. You should be proficient in leveraging Vertex AI, BigQuery ML, and Dataflow to build cost-effective, high-availability ML infrastructure.
Domain Expertise: Specialized experience with Automated Valuation Models (AVM) or high-stakes predictive modeling within Real Estate/FinTech. You understand the nuances of geospatial data, market volatility, and valuation accuracy.
Business-Technical Synthesis: Exceptional ability to bridge the gap between executive strategy and technical execution. You can translate ambiguous business goals into rigorous technical roadmaps and ROI-driven engineering projects.
Operational Excellence: Strong advocate for MLOps best practices, including CI/CD for machine learning, automated model monitoring, and robust data governance.
Communication & Influence: Masterful interpersonal skills with the ability to influence stakeholders at the C-suite level and foster a collaborative environment across cross-functional product and data science squads.

Annual Pay Range:

162,400 - 195,000 USD

Application Window:

This opportunity is expected to remain posted through the date identified below, subject to business needs.

2026-03-27

Thrive with Cotality

At Cotality, we offer more than just a job, we provide a benefits experience designed to support your whole self. From a flexible working model to competitive time off and standout health coverage with meaningful perks and growth opportunities, our package is built to help you thrive at work and in life.

Highlights, depending on role classification, include:

Time off: Generous PTO and 11 paid holidays, plus well-being and volunteer time off.
Family Support: Up to 16 weeks of fully paid parental leave and a baby stipend.
Health: Multiple medical plan options with mental health and wellness support offerings.
Retirement: 401(k) with company match and vesting after one year.
Financial Perks: $400 annual well-being stipend and tuition assistance up to $5,250.
Extras: Recognition Rewards, Referral bonuses, exclusive discounts and more!

Cotality is an Equal Opportunity employer committed to attracting and retaining the best-qualified people available, without regard to race, color, religion, national origin, gender, sexual orientation, gender identity, age, disability or status as a veteran of the Armed Forces, or any other basis protected by federal, state or local law. Cotality maintains a Drug-Free Workplace.

Cotality is fully committed to a work environment that embraces everyone’s unique contributions, experiences and values. We offer an empowered work environment that encourages creativity, initiative and professional growth and provides a competitive salary and benefits package. We are better together when we support and recognize our differences.

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Director, ML Engineering