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Data Labellers for AI training

Sapien AiKansas, OKApril 12th, 2026
Overview We are seeking a meticulous and attentive Data Labeler to join our team. The ideal candidate will be responsible for tagging and labeling various types of data, including text, images, and videos, to improve the accuracy of our machine learning models. This role requires a keen eye for detail, the ability to work with precision under tight deadlines, and a solid understanding of the specific domain or industry we are focusing on. Responsibilities Accurately label and annotate data according to predefined criteria and guidelines. Review and verify data for accuracy and consistency. Work closely with data scientists and machine learning engineers to understand the requirements and purposes of data labeling tasks. Maintain detailed documentation of labeling guidelines and processes. Provide feedback to improve data collection and labeling tools and processes. Participate in quality assurance checks to ensure the high quality of labeled data. Stay updated on industry trends and advancements in data labeling technologies and methodologies. Qualifications Excellent attention to detail and accuracy. Strong analytical and critical thinking skills. Ability to work independently and as part of a team. Good communication skills, with the ability to clearly explain complex concepts. Knowledge of machine learning concepts and the specific domain (e.g., healthcare, finance, automotive) is a plus. We Offer Opportunities for professional development and career growth. A dynamic and collaborative work environment. Access to cutting-edge technology and methodologies in the field of AI and machine learning. Flexible hours Working from home If interested, please fill out this Google form: https://forms.gle/Zjgt7EBEiberwk9A9 . Thank you! Job Types: Full-time, Part-time Pay: $8.00 - $12.00 per hour Benefits: Flexible schedule Compensation package: Bonus opportunities Performance bonus Experience level: No experience needed Schedule: 4 hour shift Work Location: In person