Note: The job is a remote job and is open to candidates in USA. Fingerprint empowers enterprises to detect and stop online fraud through accurate device intelligence and identification capabilities. The Engineering Manager will lead the multidisciplinary Identification Accuracy team, own its roadmap, drive production machine learning model improvements, and partner with engineering, product, and customer-facing teams.
Responsibilities
- Lead and grow the Identification Accuracy team — a multidisciplinary group of ML Engineers, Data Scientists, Analysts, and Analytics Engineers — fostering psychological safety, technical excellence, and a culture of continuous improvement
- Own the team's roadmap in close partnership with senior engineering leadership and cross-functional stakeholders, driving innovative solutions to identification-specific challenges and continuously raising the bar on model quality
- Drive model accuracy outcomes by enabling your team to design, train, evaluate, and ship ML models that improve identification accuracy at scale across billions of devices
- Build bridges across the organization — partnering closely with the Identification Engineering team (who operates the API your models power) as well as Product, and customer-facing teams to translate customer needs into technical priorities. Communicate effectively across technical and non-technical audiences, translating model performance and roadmap tradeoffs into language that resonates with business stakeholders and executive leadership
Skills
- Minimum of2 years of experience in a leadership role in a ML or data science team in an agile, fast-paced environment
- At least 5 years of professional experience in software engineering, machine learning, or a related technical discipline
- Demonstrated ability to lead technical teams that ship production ML systems — from data pipelines and feature engineering through model training, evaluation, and deployment
- Proven track record of building and developing high-performing, multidisciplinary teams including engineers, data scientists, and/or analysts
- Strong communication skills with the ability to translate complex model behavior, data quality issues, and technical tradeoffs to both technical teammates and non-technical stakeholders
- Demonstrated success driving outcomes in fast-moving, scaling environments where priorities evolve and ambiguity is the norm
- Experience managing teams that work with large-scale behavioral or event data in a production setting
- Familiarity with ML infrastructure and MLOps tooling — experiment tracking (e.g., MLflow), feature stores, model registries, and CI/CD pipelines for ML
- Hands-on experience with data stack technologies such as dbt or similar analytics engineering tooling
- Comfort working closely with platform and API engineering teams to understand downstream requirements and latency constraints
- Fingerprint teammates need to be authorized to work from their home location
- Background in fraud detection, identity, or trust & safety domains is a plus but not required
Benefits
- Fingerprint is a globally dispersed, 100% remote company.
Company Overview