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Label Your Data

Broad/Unclear specialization

Quick facts

Company
Label Your Data
Service type
Data annotation / AI training data
Specialties
Image, Text
Hiring status
Both: hires workers and takes vendor projects
Website
https://labelyourdata.com/
Careers
Unavailable
Profile last verified
2026-01-29

Application process overview

Label Your Data is a Ukraine-headquartered annotation services company founded in 2020 that provides image, video, text, and audio labeling for computer vision and NLP, with offices across Europe, LATAM, and Africa. Rather than a crowd platform, the company employs project-based annotators through a managed-service model, and also operates Remoter.me as a jobs portal for visual-AI annotation work.

Key findings

Application Process: Candidates apply through posted roles on Jobitt, Workable, Himalayas, or the company careers page; the path is a standard recruiter-led interview rather than open self-serve signup.<br><br>Assessments: Role-specific trial tasks and guideline-based tests are used to confirm attention to detail and tool proficiency before assignment to a live project.<br><br>Job Types / Expertise: Project Data Annotator roles covering bounding boxes, polygons, segmentation, transcription, and multilingual text tagging; the company claims 55+ languages and a 200+ specialist team.<br><br>Compensation: Paid as project-based contract or employee work rather than per-task micropayments; Glassdoor shows a compensation rating of 4.7/5 from annotator specialists.<br><br>Flexibility: Reviews consistently mention flexible hours and remote work, with internal promotion from annotator to team-lead cited as common.<br><br>Challenges / Concerns: Work is tied to specific client projects, so availability depends on the pipeline; non-EU/LATAM/Africa applicants may see fewer openings.<br><br>Legitimacy: Verified corporate entity with named clients, ISO certifications, and consistent positive Glassdoor feedback (58+ reviews).

Conclusion

Label Your Data is a legitimate managed-service annotation vendor rather than a gig platform, which tends to produce more stable, salaried-style work for accepted annotators. The upside is genuine training, team support, and internal growth; the downside is that you have to be hired through a formal process and geography matters. For people in its operating regions it compares favorably to crowd platforms on pay predictability and review scores. Outside those regions, opportunities are thinner. Overall a credible employer for annotation work when roles are open.