Engineering Manager, Identification Accuracy

Responsibilities

• Lead and grow the Identification Accuracy team, including ML Engineers, Data Scientists, Analysts, and Analytics Engineers
• Own the team's roadmap in partnership with senior engineering leadership and cross-functional stakeholders
• Drive model accuracy outcomes by enabling the design, training, evaluation, and shipping of ML models at scale
• Partner with Identification Engineering, Product, and customer-facing teams to translate customer needs into technical priorities
• Communicate complex model behavior and technical tradeoffs to both technical and non-technical stakeholders

Requirements

• Minimum 2 years of experience in a leadership role within an ML or data science team
• At least 5 years of professional experience in software engineering, machine learning, or a related technical discipline
• Demonstrated ability to lead technical teams shipping production ML systems
• Proven track record of building and developing high-performing, multidisciplinary teams
• Strong communication skills for translating complex data and model behavior to stakeholders
• Success driving outcomes in fast-moving, scaling environments

Preferred Qualifications

• Experience managing teams working with large-scale behavioral or event data in production
• Familiarity with ML infrastructure and MLOps tooling (e.g., MLflow, feature stores, model registries, CI/CD)
• Background in fraud detection, identity, or trust & safety domains
• Hands-on experience with data stack technologies such as dbt
• Experience working with platform and API engineering teams regarding latency and downstream requirements

About the Company

Fingerprint empowers developers to stop online fraud at the source by building world-class APIs for identification and fraud detection. We are a globally dispersed, 100% remote company with a strong open-source focus.