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Machine Learning Engineer II
Summary by AIEngineer.careers
Machine Learning Engineer II is a Machine Learning Engineer role (full-time). with ClearML. in NEW YORK, US. Compensation shown: $180K–$220K. Imported listing (source: zerogtalent.com). Apply on the employer's site (zerogtalent.com).
Imported listing (source: zerogtalent.com) · Apply on zerogtalent.com
NEW YORK · US
$180K–$220K
Full-time
MID
The sections below reproduce the third-party job description for reference. AIEngineer.careers does not write or control this text.
Imported job description
Sourced from zerogtalent.com
CLEAR is seeking an experienced Machine Learning Engineer to build and enhance its secure identity platform. The role involves designing, building, and deploying ML models for document and image processing and fraud detection, as well as developing robust data pipelines. You will own architectural decisions, collaborate with product stakeholders, and drive continuous improvement across ML systems.
Responsibilities
- Own and drive the foundational work of a ML system at CLEAR
- Design, build and deploy ML models for document and image processing and fraud detection
- Develop and implement robust data pipelines at various scales, including collection, pre-processing, transformation, and feature engineering
- Partner with product and other stakeholders to uncover requirements, innovate, and solve complex problems
- Take ownership of architectural decision-making and drive continuous improvement in technology and processes
Requirements
- 3+ years of experience building, operating, and scaling ML models for consumer applications
- Experience designing, implementing, and scaling complex data pipelines for ML models and evaluating performance
- Expertise in best practices for feature engineering, model development/deployment, and monitoring
ClearML
Berkeley · US · 43+ employees
ClearML provides an open-source, end-to-end AI infrastructure platform designed to help organizations streamline AI/ML workflows, optimize GPU infrastructure, and deploy generative AI models at scale. It supports the entire development lifecycle, from model experimentation to production monitoring.
