This is a fully remote, hourly contractor role supporting AI data and language projects on a project-based, flexible hour basis. Project scopes vary and may include:
- Data annotation: labeling, classifying, and structuring documents, tables, and other content to support AI training datasets.
- LLM evaluation: reviewing AI-generated responses for accuracy, reasoning quality, coherence, and cultural/linguistic appropriateness.
- Content generation: writing high-quality prompts and model responses to guide AI learning across diverse topics.
- Localization QA: ensuring terminology, tone, cultural nuance, and locale-specific details (units, references, names, dates) are consistently accurate across outputs.
You will apply senior-level Arabic localization and translation judgment alongside minimum C1 English proficiency to ensure terminology, tone, and cultural nuance are consistently accurate across use cases.
Profile Requirements
- Bachelor's degree or higher in Translation, Linguistics, Localization, Communications, or a related field.
- Native or near-native Arabic proficiency with strong writing and editing skills across Modern Standard Arabic and at least one dialect.
- Minimum C1 English proficiency (reading/writing) for interpreting prompts, source materials, and evaluation guidelines.
- Excellent editorial judgment in register, tone, punctuation, inclusivity, and cultural nuance, with extreme attention to detail.
- Ability to identify meaning drift, ambiguity, locale inconsistencies, and subtle errors, and to explain corrections clearly in writing.
- Ability to rigorously fact-check localized content (units, references, names, dates) using reliable sources and consistent reasoning.
- Ability to identify reasoning gaps, methodological errors, and unclear explanations even when language is fluent.
- Reliable, self-directed, and able to deliver consistent quality with clear communication and responsiveness across time zones.
Preferred Experience
- Professional localization or translation experience.
- Familiarity with MQM/LQA concepts (severity, category, and root-cause thinking) for consistent quality decisions.
- Proficiency with CAT tools and QA workflows (translation memory, termbases, automated checks).
- Previous experience with AI data training, annotation, or evaluation.
About CNTXT
AICNTXT AI builds artificial intelligence products and data solutions with a focus on making AI accurate, safe, and globally relevant for impact. Our work spans data services, custom AI solutions, and proprietary AI products, with deep expertise in Arabic-native and secure, sovereign solutions.
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