Remote Dutch Speech & Language QA Specialist

Synthires; Netherlands; Remote; EUR 37,000 - 80,000; Full time

Job summary

Synthires seeks Dutch bilingual experts to support a language and AI training project, evaluating Dutch speech for fluency, pronunciation, and linguistic authenticity. You will review AI-generated audio and provide detailed feedback from a native Dutch perspective.

No prior AI experience is required; your Dutch language expertise is what matters. This remote role offers flexible scheduling and the opportunity to contribute to high‑quality language evaluations across diverse datasets.

Qualifications

• Native-level Dutch proficiency in spoken and written form.
• Strong understanding of regional Dutch variations.
• English proficiency at B2+ for written and verbal communication.
• Excellent attention to detail and language analysis skills.
• Ability to work independently using online platforms in a remote environment.

Responsibilities

• Evaluate Dutch audio clips for nativeness, fluency, and linguistic authenticity.
• Assess pronunciation, grammar, and speech quality against native Dutch standards.
• Provide written feedback on language nuances, errors, and improvements.
• Document findings using project-specific tools and guidelines.
• Collaborate with quality assurance leads to maintain consistent evaluations.
• Maintain high attention to detail across all assessments.
• Participate in project updates and respond to clarifications as needed.

Skills

Dutch native

Regional Dutch variations

English B2+

Attention to detail

Written and verbal comms

Remote work

Job description

Synthires seeks Dutch bilingual experts to support a language and AI training project, evaluating Dutch speech for fluency, pronunciation, and linguistic authenticity. You will review AI-generated audio and provide detailed feedback from a native Dutch perspective.

No prior AI experience is required; your Dutch language expertise is what matters. This remote role offers flexible scheduling and the opportunity to contribute to high‑quality language evaluations across diverse datasets.