MyRemoteTeam Inc ยท 1 week ago
GenAI Data Rater (Multilingual)
MyRemoteTeam Inc is seeking highly skilled and experienced GenAI Data Raters to work on cutting-edge Generative AI initiatives. The role involves deep research, content evaluation, fact-checking, and prompt analysis to improve the quality and performance of Large Language Models at scale.
Responsibilities
Collaborate with GenAI researchers and engineers to understand data collection and evaluation requirements
Translate high-level research objectives into detailed evaluation workflows
Evaluate AI-generated content for linguistic quality, factual accuracy, relevance, and completeness
Conduct in-depth domain research using credible sources and LLM tools
Perform meticulous fact-checking and accuracy verification to prevent misinformation
Review and assess prompts and AI model responses for effectiveness and alignment with research goals
Provide structured, actionable feedback to improve AI model outputs
Innovate and optimize data collection and evaluation workflows to maximize efficiency and quality
Maintain high throughput while meeting strict quality standards
Work independently with minimal supervision in a fast-paced, high-impact environment
Qualification
Required
Graduate degree (mandatory)
Deep cultural and linguistic understanding of the target language and region
Native Full Professional Proficiency in reading and writing in at least one target language
Candidates must have prior (3-5 Years) hands-on experience in one or more of the following: GenAI / LLM evaluation or testing, AI data annotation or labeling projects, Linguistic evaluation or content quality review, Research, fact-checking, or editorial QA roles, Prompt review or prompt engineering, Working with AI data platforms (Appen, Toloka, TELUS AI, Scale AI, Remotasks, etc.)
Exceptional reading and writing skills in the target language
Strong analytical, research, and fact-checking capabilities
High attention to detail and commitment to quality
Clear written and verbal communication skills
Foundational understanding of AI, LLMs, NLP, and their limitations
Familiarity with AI writing and evaluation tools
Awareness of AI ethics, bias mitigation, and responsible AI practices
Ability to work with structured data and evaluation frameworks