Data Labeling Specialist (AI Training)

About The Role

What if your attention to detail could directly influence how AI systems understand the world? We're looking for Data Labeling Specialists to categorize, tag, and annotate the data that powers cutting-edge AI models — contributing to technology that's shaping the future of how machines think and communicate.

This is a fully remote, flexible contract role open to anyone with a sharp eye for detail and the ability to follow structured instructions. No prior AI or tech experience required — just consistency, focus, and a reliable internet connection.

Organization: Alignerr Type: Hourly Contract Location: Remote Commitment: 10–40 hours/week

What You'll Do

Categorize and label data — including text, images, and audio — using predefined guidelines and tag sets Annotate content accurately and consistently across large datasets Follow detailed project instructions to ensure data quality meets research standards Participate in calibration exercises to maintain accuracy benchmarks Complete task-based assignments independently on your own schedule

Who You Are

Detail-oriented with a methodical, consistent approach to repetitive tasks Able to follow structured instructions precisely and adapt to project-specific guidelines Comfortable working with web-based tools and platforms Self-motivated and reliable when working independently No prior data labeling, AI, or tech experience required

Nice to Have

Experience with quality assurance, data entry, or structured review workflows Familiarity with AI tools or annotation platforms as an end user Background in research, transcription, or content classification

Why Join Us

Work on real AI projects alongside leading research labs Fully remote and flexible — work when and where it suits you Freelance autonomy with the structure of meaningful, task-based work Contribute to AI development that has a tangible impact on how technology understands the world Potential for ongoing work and contract extension as new projects launch