CUA Quality Analysts

Employer description and requirements

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 detail-oriented CUA Quality Analysts to support a high-impact AI training and data annotation initiative. In this role, you will leverage your expertise in Computer-Using Agent (CUA) projects, data annotation workflows, and quality assurance to train annotators, enforce annotation standards, build process documentation, and drive operational excellence across AI training datasets.

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 understanding of data annotation workflows, quality metrics, and human-in-the-loop AI operations; proven ability to follow step-by-step documentation and navigate complex software applications.

Preferred Experience: Direct prior experience working on CUA projects, data annotation/labeling initiatives, and training or mentoring annotation teams.

Analytical & Operational Skills: Excellent written communication for SOP/guideline drafting, strong problem-solving abilities, meticulous attention to detail, and strict adherence to confidentiality and data-handling protocols.

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:

Quality Assurance & Review: Reviewing annotated data, conducting periodic evaluations, and providing actionable feedback to ensure strict adherence to project standards, quality metrics, and SLAs.

Training & Onboarding: Training, mentoring, and conducting onboarding sessions for data annotators on CUA project guidelines, workflows, and continuous learning programs.

Documentation & SOP Creation: Creating and maintaining training materials, annotation guidelines, and process documentation for project workflows.

Process Optimization & Calibration: Supporting pilot runs, calibration exercises, and resolving edge cases and rubric ambiguities in collaboration with QA leads and project managers.

Operational Excellence: Identifying process gaps, recommending workflow enhancements, and ensuring consistent alignment with project benchmarks and deadlines.

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.