Quality Assurance Lead (Danish)

The work

You will lead quality reviews for Danish AI-generated content and trainer QA work. You will check work against detailed rubrics and help contributors apply Danish project guidelines consistently.

The role includes written feedback, quality issue escalation, contributor onboarding, documentation, and workflow improvements for Danish-language AI training projects.

• Review Danish AI-generated content and trainer QA work against project rubrics.
• Find language, translation, formatting, tone, cultural, meaning, and instruction-following issues.
• Check grammar, spelling, fluency, terminology, register, and formatting.
• Identify mistranslations, unnatural phrasing, hallucinations, ambiguity, and inconsistent terminology.
• Give clear written feedback and escalate recurring quality problems.
• Communicate project updates and expectations to trainers and QA contributors.
• Maintain style guides, FAQs, trackers, examples, honeypots, and onboarding materials.
• Help align contributors and improve scalable Danish QA workflows.

What it pays and takes

This is an intermediate-level, remote contractor role for Danish-language quality assurance work. It is listed as part-time and requires at least 20 hours per week.

• Pay: $55 per hour.
• Location: Open to candidates in Denmark.
• Language: Fluent Danish with strong reading and writing ability.
• Communication: Strong English for guidance, feedback, and coordination.
• Experience with Danish writing, editing, translation, localization, content QA, AI training, or similar review work.
• Strong understanding of Danish grammar, spelling, punctuation, tone, register, and cultural context.
• Ability to evaluate content against rubrics and identify subtle quality issues.
• Comfort using Discord, Google Docs, Google Sheets, trackers, dashboards, and project management systems.

How it works

Apply on OpenTrain with your resume, then complete the application on the hiring site.

About AI training work

AI training work uses human review to help improve artificial intelligence systems. Language specialists evaluate examples, explain quality problems, and help models produce clearer and more useful content.