Cantonese Language Evaluator

Remotebridge; United States; Remote; USD 34,000 - 69,000; Full time

Job summary

Remotebridge is seeking Cantonese Language Evaluators to join a remote contractor team. You will evaluate Cantonese text and speech to train AI systems, providing feedback and annotations to improve model outputs. No AI background required beyond domain expertise.

You will work independently using our internal systems and contribute to high-quality language data processes. Ideal candidates are native Cantonese speakers with strong communication skills and experience in language evaluation or

Qualifications

• Native proficiency in Cantonese with strong writing and speaking skills.
• Experience in language evaluation, translation, linguistic annotation, or related language tech projects.
• Excellent written and verbal communication with keen attention to detail.
• Familiar with content moderation, transcription, or quality assessment tasks is advantageous.
• Analytical mindset with consistent evaluation criteria across samples.
• Comfort using online platforms and digital evaluation tools for data review and submission.
• Ability to work independently and manage multiple assignments to meet deadlines.

Responsibilities

• Assess Cantonese text and speech data for linguistic accuracy, fluency, and context.
• Provide detailed feedback on model outputs to identify errors and improvements.
• Participate in data annotation, labeling, and categorization for NLP development.
• Collaborate with project leads to refine tasks and evaluation criteria.
• Follow project guidelines and maintain consistency across deliverables.
• Document insights and recommendations to improve evaluation processes.
• Support ad hoc linguistic quality reviews as project needs evolve.

Skills

Cantonese native

Language evaluation

Linguistic annotation

Translation

Quality assessment

Attention to detail

Tools

Internal evaluation tools

Job description

Role Title: Cantonese Language EvaluatorRole Type: ContractorLocation: RemoteOur team is engaging Cantonese Language Evaluators to contribute to a language-focused project supporting a valued customer. In this role, you'll apply your expertise to help train next-generation AI systems. Your work will shape how models learn, reason, and perform through high-quality, real-world input. No prior experience in AI is required — your domain knowledge is what matters. As a native Cantonese speaker, you will participate in internal evaluation tasks using Our team's proprietary system, directly impacting the quality and accuracy of language technologies.

Scope of Work

• Assess Cantonese text and speech data for linguistic accuracy, fluency, and contextual appropriateness using internal tools.
• Provide detailed feedback on model outputs to identify errors, ambiguities, and improvement opportunities.
• Participate in data annotation, labeling, and categorization assignments tailored to natural language processing development.
• Collaborate with project leads to refine tasks, clarify evaluation criteria, and elevate complex language cases as needed.
• Follow established project guidelines and maintain consistency and quality across all deliverables.
• Document insights and recommendations to support continuous improvement of evaluation processes and system outputs.
• Support ad hoc linguistic quality reviews based on evolving project needs and priorities.

Preferred Qualifications

• Native proficiency in Cantonese, with strong command of written and spoken forms.
• Demonstrated experience in language evaluation, translation, linguistic annotation, or related language technology projects.
• Exceptional written and verbal communication skills, with keen attention to detail.
• Familiarity with content moderation, transcription, or quality assessment tasks is advantageous.
• Analytical mindset and ability to apply consistent evaluation criteria to diverse language samples.
• Comfort using online platforms and digital evaluation tools for data review and submission.
• Ability to work independently, manage multiple assignments, and meet project deliverables efficiently.