Director, Machine Learning

📋 Description

• Own the ML charter across identity resolution, fraud and abuse detection, risk scoring, and
• Build and grow a high-performing, globally distributed team of ML engineers; hire, coach, and
• Set the technical bar for how models get built, evaluated, deployed, and monitored — and hold the
• Push identity resolution coverage, precision, and profile classification accuracy against a
• Own IRIS model performance end-to-end: detection rate, false-positive rate, label quality, and the
• Build the ML platform layer — feature stores, training pipelines, model registry, online serving

🎯 Requirements

• 12+ years in engineering with 5+ years managing ML or data teams, including managing managers or
• An engineer at heart — can still read a training pipeline, review a feature spec, and tell when an
• Shipped ML systems that make consequential automated decisions in production, and have owned them
• Deep experience with at least one of: entity resolution / identity graphs, fraud and abuse
• Understanding of what makes ML different from software: labels are noisy and delayed, systems fail
• Opinions about evaluation — precision/recall tradeoffs on heavily imbalanced data, holdout hygiene

🎁 Benefits

• Annual bonus, equity, and benefits
• Work from home
• Remote work