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Senior Data Annotator

Rex.zone

Remote · ಪೂರ್ಣ ಸಮಯ

ಅರ್ಜಿ ಸಲ್ಲಿಸುವವರಲ್ಲಿ ಮೊದಲಿಗರಾಗಿರಿ

ಅನುಭವ
ಯಾವುದೇ
ಸಂಬಳ
USD 30 – USD 50 / hour
ತೆರೆಯುವಿಕೆಗಳು
1
ಪೋಸ್ಟ್ ಮಾಡಲಾಗಿದೆ
7 ಗಂಟೆಗಳ ಹಿಂದೆ
ಕೆಲಸದ ಮೋಡ್
ಮನೆಯಿಂದ ಕೆಲಸ ಮಾಡಿ
ಪುನರಾರಂಭ
ಅರ್ಜಿ ಸಲ್ಲಿಸಲು ಕಡ್ಡಾಯ

ಕೆಲಸದ ವಿವರ

About the Role

Rex.zone invites applications for a Senior Data Annotator to enhance AI and ML model training through meticulous data labeling and review efforts. This role is crucial in delivering top-quality, guideline-compliant annotated datasets for natural language processing, computer vision, and content safety applications.

Key Responsibilities

  • Lead advanced-level annotation and review processes across text, image, and multimodal data collections.
  • Conduct Reinforcement Learning from Human Feedback (RLHF) preference ranking and evaluate large language models following strict rubrics.
  • Execute quality assurance audits, calibration exercises, and continuous monitoring to uphold annotation standards.
  • Detect and report gaps in guidelines, catalog complex edge cases, and suggest improvements to rubric clarity.
  • Monitor consistency among annotators and resolve discrepancies via calibration protocols.
  • Participate in prompt evaluations assessing helpfulness, safety, and adherence to policies.
  • Engage in content safety labeling and the management of sensitive topic classifications.
  • Collaborate with engineering and data operations teams to enhance annotation tools, optimize workflows, and improve error identification.

Required Qualifications

  • Proven experience in data annotation, labeling, or quality assurance for machine learning datasets.
  • Aptitude to rigorously apply detailed rubrics and maintain compliance with annotation guidelines.
  • Understanding of RLHF processes, preference data appraisal, and large language model evaluation techniques.
  • Strong written communication skills necessary for documenting judgments and complex cases.
  • Hands-on experience with NLP tasks such as named entity recognition and/or computer vision annotation methods like bounding boxes and segmentation.

Quality Metrics

Performance is evaluated through regular audits, inter-annotator agreement assessments, rubric adherence, calibration rounds, and error rate analysis to ensure the highest integrity of training data for downstream models.

Remuneration

The position offers a competitive hourly wage ranging from $30 to $50 USD.

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