The Work
You will oversee quality and consistency across Dutch-language AI training and localization projects. This hands-on role combines rubric-based review, written feedback, documentation, and support for reviewers and contributors.
You will also identify recurring quality issues, communicate workflow updates, support onboarding, and help improve processes for Dutch-language projects.
- Review Dutch AI training outputs and trainer or QA submissions for accuracy, fluency, grammar, spelling, tone, and meaning.
- Check work against project guidelines, formatting rules, and project-specific rubrics.
- Give clear written feedback to trainers and QAs.
- Track recurring issues and maintain style guides, FAQs, trackers, examples, and honeypots.
- Support onboarding, contributor activation, and workflow improvements.
What It Pays And Takes
This is a part-time contractor role for someone with strong Dutch language judgment and experience reviewing language or AI-related content. The work requires careful attention to detail and clear communication with remote teams.
- Pay: $50 per hour.
- Schedule: 20+ hours per week.
- Location: Open to candidates in Belgium and the Netherlands.
- Languages: Fluent Dutch with strong reading and writing ability, plus strong English communication.
- Experience: Dutch writing, editing, translation, localization, content QA, AI training, or a related language-review workflow.
- Knowledge: Dutch grammar, spelling, register, tone, and cultural context.
- Work style: Comfortable with remote teams, documentation, and fast-moving QA processes.
- Helpful: Experience with Netherlands Dutch and/or Belgian Dutch (Flemish).
- Helpful: Experience leading or supporting reviewers, annotators, editors, trainers, or QAs.
- Helpful: Familiarity with data annotation, large language models, prompt or response evaluation, or rubric-based AI quality review.
How It Works
Apply on OpenTrain with your resume, then complete the application on the hiring site.
About AI Training Work
AI training is the human work behind systems that generate and understand language. People review examples, rate model responses, and prepare feedback so AI systems become more accurate, clear, and useful; experienced language reviewers are needed for detailed judgments about grammar, tone, and meaning.