AI Data Quality Control Coordinator

1 hour, 51 minutes ago
Freelance
Mid Level
Artificial Intelligence and Machine Learning
Welo Global

Welo Global

Welo Global specializes in providing enterprise localization, AI training data, and multilingual content solutions, leveraging a portfolio of specialized global brands to meet diverse customer needs in the AI and language services industry.

Professional Services
Founded 1997

Description

  • Perform sampling and quality checks on annotated datasets across text, image, audio, and video formats.
  • Identify, log, categorize, and track annotation defects through corrective action and rework closure.
  • Validate re-tests and document quality outcomes for datasets and annotation workflows.
  • Coordinate onboarding, calibration sessions, and refresher training for annotators and reviewers.
  • Maintain annotation guidelines, SOPs, and rubrics with proper version control and communication.
  • Prepare client-ready quality reports, including tables, charts, summaries, and consistent formatting.
  • Liaise with Project Managers and Operations teams on timelines, reporting, and audit requirements.
  • Manage access permissions for annotation tools, QA platforms, and shared repositories.
  • Support vendor coordination by handling documentation requests, SLAs, and quality expectations.
  • Identify process gaps and recommend improvements such as QA checklists, templates, and sampling approaches.

Requirements

  • Bachelor’s degree in any discipline, with Data Science, Computer Science, Linguistics, or related fields preferred.
  • 2–4 years of experience in quality control or quality assurance within AI data annotation, data labeling, or content moderation.
  • Strong understanding of annotation workflows such as bounding boxes, segmentation, classification, and transcription.
  • Familiarity with QA metrics including accuracy, precision/recall, F1 score, and inter-annotator agreement.
  • Proficiency in MS Excel or Google Sheets, including pivot tables, dashboards, and data analysis.
  • Experience with annotation tools such as Labelbox, CVAT, Scale AI, or similar platforms.
  • Exposure to NLP, Computer Vision, or Speech datasets.
  • Basic understanding of machine learning workflows and the data lifecycle.
  • Experience working with global clients and distributed or remote annotation teams.
  • Strong attention to detail, communication, coordination, and organizational skills in a fast-paced environment.

Benefits

  • Freelance remote work arrangement.
  • Opportunity to contribute to cutting-edge AI projects.
  • Chance to build expertise in data quality and annotation processes.
  • Work with a global, multilingual organization supporting major AI systems.

Interested in this position?

Apply directly on the company website

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