Engineering Manager, Identification Accuracy

This is a fully remote position, open to applicants in United States.

📋 Description

• Lead and develop the multidisciplinary Identification Accuracy team composed of ML Engineers, Data Scientists, Analysts, and Analytics Engineers.

• Cultivate an environment of psychological safety, technical excellence, and continuous improvement.

• Manage the team’s roadmap in collaboration with senior engineering leadership and cross-functional stakeholders.

• Oversee the design, training, evaluation, and deployment of ML models aimed at enhancing identification accuracy across billions of devices.

• Collaborate with Identification Engineering, Product, and customer-facing teams to align customer requirements with technical priorities.

• Convey model performance and roadmap considerations to technical, business, and executive stakeholders.

⛳️ Requirements

• A minimum of 2 years of experience in a leadership capacity within an ML or data science team in an agile, fast-paced setting.

• At least 5 years of professional experience in software engineering, machine learning, or a related technical field.

• Proven ability to lead technical teams in delivering production ML systems, encompassing data pipelines and feature engineering through to model training, evaluation, and deployment.

• Demonstrated success in building and nurturing high-performing multidisciplinary teams, including engineers, data scientists, and/or analysts.

• Excellent communication skills for articulating complex model behaviors, data quality challenges, and technical trade-offs to both technical and non-technical audiences.

• Experience in driving results in dynamic, scaling environments with shifting priorities and uncertainty.

• Preferred: experience working with large-scale behavioral or event data in production settings.

• Preferred: familiarity with ML infrastructure and MLOps tools, such as MLflow, feature stores, model registries, and ML CI/CD pipelines.

• Preferred: a background in fraud detection, identity management, or trust and safety.

• Preferred: practical experience with dbt or similar analytics engineering tools.

• Preferred: comfort in collaborating with platform and API engineering teams regarding downstream requirements and latency constraints.

• Must possess authorization to work from the candidate's home location; Fingerprint does not sponsor visas.

🏝️ Benefits

• 100% remote work.

• Inclusive work environment.

• Opportunities to collaborate with a globally dispersed team.

• Compensation is based on relevant experience, education, certifications/licenses, skills, training, and market conditions.