Director, ML Engineering

About the role

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.

Responsibilities

• Mentor and scale a dual-discipline team of ML Engineers and Operations specialists, fostering a culture of technical excellence and rigorous engineering standards.

• Direct the end-to-end lifecycle of custom Automated Valuation Models, from architectural design in GCP to production deployment and real-time inference.

• 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.

• Oversee the engineering of automated feature stores and data pipelines, ensuring high-fidelity datasets for training, validation, and backtesting.

• Partner with Data Science and Product teams to solve bottlenecks in model latency, throughput, and cost-efficiency.

• Implement sophisticated monitoring frameworks to detect feature drift and model decay, ensuring the long-term accuracy of valuation outputs.

• Translate complex technical roadmaps into actionable business value for executive leadership and cross-functional partners.

Qualifications

• Strategic Leadership: 8+ years of experience in ML or Software Engineering, with at least 3+ years in a dedicated people management role. 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. 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. Understanding of geospatial data, market volatility, and valuation accuracy.

• Business-Technical Synthesis: Exceptional ability to bridge the gap between executive strategy and technical execution. Ability to 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.

Pay

Annual Pay Range: 162,400 - 195,000 USD

Schedule

Not specified

Benefits

Cotality offers a comprehensive benefits package including:

• Generous PTO and 11 paid holidays, plus well-being and volunteer time off.

• Up to 16 weeks of fully paid parental leave and a baby stipend.

• Multiple medical plan options with mental health and wellness support offerings.

• 401(k) with company match and vesting after one year.

• $400 annual well-being stipend and tuition assistance up to $5,250.

• Recognition Rewards, Referral bonuses, exclusive discounts and more!

Equal Opportunity Employer

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.