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The Role
Review and post-edit machine-translated Spanish (US) customer service content for accuracy and naturalness. Rate MT output, produce high-quality human reference translations, follow style guides and terminology, and report recurring quality issues and batch-level trends.
Summary Generated by Built In
We are looking for experienced language professionals to support an ongoing project focused on reviewing and refining Spanish (United States) customer service content. This role involves improving machine-translated materials to ensure accuracy, natural language, and alignment with project guidelines.
What you’ll do
Edit and review machine-translated customer service content with a high level of accuracy and consistency.
Evaluate MT output quality and apply severity ratings when required, following project guidelines.
Produce high-quality human translations as reference data for model training and quality evaluation.
Follow provided style guides, tone rules, and terminology requirements.
Identify and report recurring MT quality issues and batch-level trends.
Project details
Language: Spanish (United States)
Content type: Customer service content (general)
Project duration: OngoingThis role involves intermittent work, with tasks assigned on an ad hoc basis throughout the year depending on client needs. Volumes and timing may vary.
Hourly rate: $33.09
Requirements
- Native proficiency in Spanish (United States) and strong English skills.
- Experience in translation, localization, or MT post-editing.
- Familiarity with machine translation quality evaluation and error identification.
- Strong attention to detail and a quality-focused mindset.
- Ability to work independently in an online environment.
Skills Required
- Native proficiency in Spanish (United States) and strong English skills.
- Experience in translation, localization, or MT post-editing.
- Familiarity with machine translation quality evaluation and error identification.
- Strong attention to detail and a quality-focused mindset.
- Ability to work independently in an online environment.
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