ML Engineer II — Secure Identity & Fraud Detection

CLEAR - Corporate; New York (NY); On-site; USD 180,000 - 220,000; Full time

Benefits offered by this job

meals and snacks

learning & development stipend

comprehensive healthcare plans

family building benefits

flexible time off

OneMedical memberships

401(k) retirement plan with employer

Job summary

CLEAR is building the secure identity company of the future, transforming how people live, work and travel through safer, frictionless experiences in physical and digital spaces. We’re seeking an experienced Machine Learning Engineer to design, implement, test and deploy ML systems that power our networked identity platform, with privacy and security at the core.

This NYC role requires five days in the office.

Qualifications

• 3+ years of experience building, operating and scaling ML models for consumer applications, end-to-end systems experience preferred.
• Expertise in feature engineering, model development, deployment and monitoring.

Responsibilities

• Own and drive the foundational work of a ML system at CLEAR.
• Design, build and deploy ML models for applications such as document and image processing, fraud detection.
• Develop and implement robust data pipelines at various scales (collection, pre-processing, transformation, feature engineering).
• Partner with product and stakeholders to uncover requirements and solve complex problems.
• Maintain ownership and drive architectural decisions with continuous improvement.

Skills

ML systems

Data pipelines

Feature engineering

Stakeholder communication

Mentoring

Autonomy

Ambiguity tolerance

Job description

CLEAR is building the secure identity company of the future, transforming how people live, work and travel through safer, frictionless experiences in physical and digital spaces. We’re seeking an experienced Machine Learning Engineer to design, implement, test and deploy ML systems that power our networked identity platform, with privacy and security at the core.

This NYC role requires five days in the office.