Remote AI Content Annotator (Ukrainian, Poland)

Welocalize; Kraków; On-site; PLN 46,000 - 56,000; Part time

Benefits offered by this job

Short-term, project-based

Flexible remote work within Poland

Guidelines, training materials, and on

ongoing support from project leads

Job summary

Welocalize, via the Welo Data unit, seeks Ukrainian reviewers to annotate multilingual and multimedia content for training AI systems. The role is freelance and remote, based in Poland, with compensation at $10/hour.

You will review AI outputs, ensure quality, and provide actionable feedback to improve guidelines and workflows. Ideal candidates are native Ukrainian speakers with strong English writing skills, attention to detail, and experience in data labeling, localization, or quality

Qualifications

• Native-level Ukrainian proficiency.
• Strong written English skills.
• Experience in annotation, content review, QA, data labeling, localization, or related fields.
• Ability to follow detailed guidelines and meet deadlines.

Responsibilities

• Review and annotate multilingual content across text, image, audio, and video.
• Perform quality checks for accuracy and consistency with project guidelines.
• Flag edge cases and provide feedback to improve outputs and instructions.
• Create and refine high-quality datasets to train AI models.
• Participate in calibration sessions and quality alignment activities.
• Communicate clearly to improve workflows and tools.

Skills

Ukrainian

English writing

Attention to detail

QA

Data labeling

Localization

Tools

Annotation platforms

Productivity tools

Job description

Welocalize, via the Welo Data unit, seeks Ukrainian reviewers to annotate multilingual and multimedia content for training AI systems. The role is freelance and remote, based in Poland, with compensation at $10/hour.

You will review AI outputs, ensure quality, and provide actionable feedback to improve guidelines and workflows. Ideal candidates are native Ukrainian speakers with strong English writing skills, attention to detail, and experience in data labeling, localization, or quality