CUA Data Annotation Trainer at Turing

CUA Data Annotation Trainer | Contractor | Worldwide Remote | 2-Week Engagement

Turing is seeking a skilled and detail-oriented CUA Data Annotation Trainer to support a high-impact AI training initiative. In this role, you will train and mentor annotators, build process documentation, enforce quality standards, and drive operational excellence across complex AI data workflows involving Computer-Using Agent (CUA) projects.

About Turing

Turing's mission is to accelerate superintelligence to drive real economic progress. Headquartered in San Francisco, Turing partners with frontier AI labs to generate high-quality data, evaluations, and reinforcement learning environments that improve model capabilities in coding, reasoning, tool use, and multimodality. Turing also works with Fortune 500 enterprises to build and deploy end-to-end agentic AI systems inside mission-critical workflows.

Key Responsibilities

• Training & Onboarding: Train, mentor, and onboard data annotators on CUA project guidelines, workflows, and continuous learning programs.
• Documentation: Create and maintain training materials, SOPs, and project-specific annotation guidelines.
• Quality Monitoring: Review annotated data, monitor annotator performance, conduct quality evaluations, and provide actionable feedback to enforce standards and SLAs.
• Operational Support: Support pilot runs, calibration exercises, process gap identification, and workflow enhancements.
• Problem Resolution: Collaborate with QA teams and project managers to troubleshoot workflow issues and resolve edge cases and rubric ambiguities.

Requirements

• Personal computer with a minimum of 16GB RAM, stable high-speed internet, and access to Windows, Linux, or macOS.
• Strong ability to follow step-by-step documentation, execute tasks precisely, and maintain strict data confidentiality protocols.
• Prior experience with CUA projects, data annotation/labeling, and training or mentoring annotation teams is strongly preferred.
• Deep understanding of annotation quality metrics, AI/ML human-in-the-loop workflows, and excellent written communication skills for drafting SOPs.
• Bachelor's degree or equivalent practical experience; background in AI evaluation, data annotation, content review, or quality assurance preferred.

Engagement Details

• Commitment: 40 hours per week, with at least 4 hours of daily overlap with the PT time zone.
• Type: Contractor/Freelancer assignment — task-based (no medical or paid leave benefits).
• Duration: 2 weeks.

Application Process

Shortlisted candidates will receive a Job Interest Form. Final selected candidates will be contacted with next steps and onboarding requirements.