Engineering Manager, Identification Accuracy

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Engineering Manager leading a team of ML engineers and data scientists for fraud detection model improvement. Overseeing technical excellence and collaboration with cross-functional teams in a 100% remote environment.

Posted 5/21/2026full-timeRemote • 🇺🇸 United StatesMid-LevelSenior💰 $159,000 - $215,000 per yearWebsite

About the role

Key responsibilities & impact

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.

Requirements

What you’ll need

Minimum of 2 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.

Benefits

Comp & perks

Competitive salary
Open-source project involvement
100% remote work
Inclusive work environment

ATS Keywords

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Hard Skills & Tools

machine learningdata sciencesoftware engineeringmodel trainingmodel evaluationmodel deploymentdata pipelinesfeature engineeringproduction ML systems

Soft Skills

leadershipcommunicationteam buildingcollaborationproblem-solvingadaptabilitypsychological safetycontinuous improvement