Director, Machine Learning
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The role
Lead end-to-end development and deployment of ML/DL models for fraud detection and risk mitigation, including data acquisition, feature engineering, experimentation, and production monitoring.
Architect secure, reliable, and scalable ML systems optimized for real-time performance in high-stakes environments.
Partner with Product Management and Engineering to define AI/ML strategies, translate business problems into ML solutions, and align on roadmaps.
Drive model performance tracking and continuous improvement through rigorous evaluation, iteration, and lifecycle management.
Steer cross-functional Agile teams, mentor a geographically distributed group of ML engineers and data scientists, and drive engineering excellence and delivery metrics.
Stay ahead of AI/ML advances, shape long-term technical strategy, and contribute to talent development and leadership across the team.
Architect secure, reliable, and scalable ML systems optimized for real-time performance in high-stakes environments.
Partner with Product Management and Engineering to define AI/ML strategies, translate business problems into ML solutions, and align on roadmaps.
Drive model performance tracking and continuous improvement through rigorous evaluation, iteration, and lifecycle management.
Steer cross-functional Agile teams, mentor a geographically distributed group of ML engineers and data scientists, and drive engineering excellence and delivery metrics.
Stay ahead of AI/ML advances, shape long-term technical strategy, and contribute to talent development and leadership across the team.
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