Cultural & Linguistic Expert

Work Location: US (Remote)
Work Schedule: Flexible, project-based
Engagement Model: Contract / Part-time consulting
Start Date: ASAP

Role Summary

We are seeking native speakers and cultural experts to support Generative AI data creation, evaluation, and query vetting projects. As a Culture and Linguist Expert, you will apply your deep linguistic, cultural, and societal knowledge to help train, evaluate, and improve large language models (LLMs). Your contributions will ensure AI systems deliver responses that are culturally accurate, context-aware, unbiased, and reliable.

This role requires close collaboration with AI researchers and engineers, rapid execution of workflows, and a strong focus on quality, accuracy, and cultural nuance.

Main Responsibilities

• Generate Training Sets: Create, expand, and review culturally authentic content, including natural language queries, prompts, idiomatic expressions, and real-world conversational examples.

• Create Evaluation Sets: Design culturally nuanced prompts to test AI systems on humor, sensitive topics, taboos, regional variation, and social context.

• Benchmark AI Responses: Evaluate model outputs for cultural appropriateness, tone, factual accuracy, bias, and overall quality, providing detailed and actionable feedback.

• Query Vetting & Fact Checking: Conduct in-depth research to verify accuracy, precision, and recall, ensuring content meets high factual and informational standards.

• Framework & Workflow Development: Translate high-level research requirements into detailed workflows, helping define cultural evaluation standards and best practices.

• Data Vetting & Enrichment: Review and enrich datasets to ensure they represent diverse cultural perspectives across regions, demographics, and socioeconomic contexts.

• Bias Analysis & Ethical Review: Identify, categorize, and document cultural, social, and ethical biases in AI outputs, contributing to bias mitigation and responsible AI development.

• Cross-Functional Collaboration: Work closely with AI researchers, engineers, and peer reviewers to maximize data quality, throughput, and impact.