CUA Data Annotator

About this role

About Turing: Turing’s mission is to accelerate superintelligence to drive real economic progress. Headquartered in San Francisco, Turing works 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. In coding, Turing is the largest and longest-running data provider in the category. Turing also works with Fortune 500 enterprises across Financial Services, Life Sciences, Healthcare, Retail, Automotive, and CPG to build and deploy end-to-end agentic AI systems inside mission-critical workflows. By operating on both sides, Turing closes the loop between frontier research and enterprise deployment, turning real-world deployment signals into better data, evaluations, and more capable models. About the role We are seeking experienced and detail-oriented CUA Data Annotation Trainers to support a high-impact AI training and data annotation initiative. In this role, you will leverage your hands-on experience in Computer-Using Agent (CUA) projects, data annotation workflows, and trainer operations to train and mentor annotators, build comprehensive process documentation, enforce quality standards, and drive operational excellence across complex AI data workflows. Requirements Technical Infrastructure: Personal computer with a minimum of 16GB RAM, stable high-speed internet connection, and access to Windows, Linux, or macOS capable of running project tools securely. Core Competencies: Strong ability to follow step-by-step written documentation, execute tasks precisely, navigate a wide range of computer applications, and maintain strict confidentiality and data-handling protocols. Preferred Experience: Direct prior experience working on CUA projects, data annotation/labeling initiatives, and training or mentoring annotation teams. Analytical & Operational Skills: Deep understanding of annotation quality metrics and review methodologies, familiarity with AI/ML human-in-the-loop workflows, excellent written communication for drafting SOPs/guidelines, and strong problem-solving skills to operate independently in a fast-paced environment. Responsibilities: In this role, you will be part of a specialized functional pod responsible for creating, reviewing, and maintaining high-quality training and evaluation data for AI models. Your day-to-day responsibilities will include: Training & Onboarding: Training, mentoring, and conducting onboarding sessions for data annotators on CUA project guidelines, workflows, and continuous learning programs. Documentation & Materials Creation: Creating and maintaining training materials, SOPs, and project-specific annotation guidelines. Quality & Performance Monitoring: Reviewing annotated data, monitoring annotator performance, conducting periodic quality evaluations, and providing actionable feedback to enforce standards and SLAs. Operational & Calibration Support: Supporting pilot runs, calibration exercises, process gap identification, and workflow enhancements to optimize team outputs. Problem Resolution: Collaborating with QA teams and project managers to troubleshoot workflow issues and resolve edge cases and rubric ambiguities. Education & Experience: Bachelor's degree or equivalent practical experience in any field. Experience in AI evaluation, data annotation, content review, quality assurance, or a related analytical role is preferred. Offer Details: Commitments Required: 40 hours per week, with some overlap with PT Time Zone (4 hours/day). Engagement type: Contractor assignment/freelancer (no medical/paid leave), Task Based. Duration: 2 weeks. Application Process: Shortlisted candidates will be sent a Job Interest Form . Final selected candidates will be contacted with the next steps and onboarding requirements.