CLEAR - Corporate
Machine Learning Engineer II
About this role
CLEAR seeks an experienced Machine Learning Engineer II to design, build, and deploy ML models for their secure digital identity platform. You'll own end-to-end ML systems covering document/image processing and fraud detection while partnering with product teams to drive innovation in privacy-preserving identity solutions.
What you'll do
- Own foundational ML system work and drive architectural decision-making for CLEAR's platform
- Design, build, and deploy ML models for document processing, image analysis, and fraud detection
- Develop and scale data pipelines including collection, preprocessing, transformation, and feature engineering
- Partner with product and stakeholders to uncover requirements and solve complex problems
- Mentor less experienced team members and collaborate across engineering teams
- Monitor model performance and implement best practices for deployment and continuous improvement
What they're looking for
- Machine learning model development and deployment (3+ years)
- Python programming
- Data pipeline design and scaling
- Feature engineering and model evaluation
- AWS SageMaker and MLflow
- SQL and data warehouse tools (Postgres, Snowflake, dbt)
- Technical communication to mixed audiences
- End-to-end ML system architecture
Benefits
- Comprehensive healthcare plans and free OneMedical memberships for you and dependents
- Family building benefits including fertility and adoption/surrogacy support
- Flexible time off and 401(k) with employer match
- Learning and development stipend and reimbursement programs
- Office meals and snacks
- New hire equity package with refresh grants
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CLEAR - Corporate
CLEAR operates a secure identity platform serving 38+ million members across travel, enterprise, and financial services. The company is hiring fullstack and infrastructure software engineers to build and maintain scalable systems, with a focus on deployment processes, cloud infrastructure, and end-to-end technical project ownership.
- Website
- clearme.com
Likely interview questions
- Walk us through an end-to-end ML system you've built from data collection through production deployment—what were the biggest challenges?
- How do you approach feature engineering at scale, and what tools or frameworks have you used to manage complex data pipelines?