Kannada Language Expert
SME Careers
Remote
This role is with SME Careers, a fast-growing AI Data Services company and subsidiary of SuperAnnotate, delivering training data for many of the world’s largest AI companies and foundation-model labs. Your Kannada expertise directly helps improve the world’s premier AI models by making their Kannada language output more natural, reliable, culturally accurate, and clearly written.
Selection process involves an AI interview, a domain-specific task, and an interview with a recruiter.
Key Responsibilities
- Develop AI Training Content: Create prompts and gold-standard Kannada answers across multiple domains (general knowledge, customer support, education, conversational writing).
- Optimize AI Performance: Evaluate and rank AI outputs to improve fluency, correctness, tone match, and cultural appropriateness.
- Ensure Model Integrity: Detect unsafe or misleading content, factual hallucinations, bias, and policy-risk language; validate reliability across use cases.
- Bachelor’s degree (or higher) in Linguistics, Kannada/English Literature, Communications, Journalism, Translation, or a related field (or equivalent professional experience).
- Native or near-native Kannada proficiency (reading and writing required).
- Strong professional proficiency in English (minimum C1) to follow guidelines and provide detailed feedback in English.
- 3+ years of professional experience in writing, editing, localization, translation, content QA, journalism, education, or related language-focused work.
- Deep understanding of Kannada grammar, spelling conventions, punctuation, and style—able to explain why something is wrong and how to fix it.
- Comfortable handling multiple registers (formal/informal), regional variation (e.g., Bengaluru/standard usage vs regional dialect influence), and audience adaptation (India vs diaspora).
- High attention to detail when spotting subtle meaning shifts, hallucinated claims, or culturally awkward phrasing.
- Reliable, self-directed, and able to deliver consistent quality in an hourly, remote contractor workflow across time zones.
- Prior experience with AI data training/annotation, translation QA, editorial QA, or rubric-based evaluation is strongly preferred.