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Language : -German Language
Minimum Time Commitment Per day : 4-5 hours per day
Pay rate per hour : 4 USD per hour
About the Role
We are looking for someone who is detail oriented and has strong understanding of German language. In this role, you will help improve AI systems by reviewing and creating language data. Your work will help train large language models (LLMs) and other NLP tools.
Key Responsibilities
• Create or edit content such as grammar explanations, sentence examples, and notes about how language works
• Find and fix issues related to grammar, unclear meaning, and bias
• Check AI outputs for fluency, accuracy, tone, and correctness
• Label and annotate text with linguistic information (syntax, meaning, context, etc.)
• Do linguistic research and share short summaries
• Review AI results and identify patterns or errors using linguistic knowledge
Qualifications
• Strong foundation in linguistics (syntax, semantics, phonology, morphology, pragmatics, sociolinguistics, etc.)
• Experience in computational linguistics, corpus work, data annotation, or LLM training is helpful
• Excellent writing and communication skills
• Detail-oriented and strong understanding of language structure.
If you are interested in this opportunity, please reply to the given questions:
* Are you native of India
* Are you fluent in German Language
*Can you commit to a minimum of 4-5 hours per day
* Does you bank account accepts payment in USD currency(Payment will be direct bank transfer in USD only)
Job ID: 148679053
Skills:
Python, AI Data Annotation, AI ML concepts
Skills:
audio transcription , text classification , Label Studio, LLMs, data annotation, ELAN, NER entity tagging, Doccano, sentiment tagging
Skills:
Academic Writing, Linguistics, data annotation, translating, Writing, teaching, editing
Skills:
Sql, Python, annotation tools, data annotation, Quality Control
Skills:
annotation platforms, medical data annotation, Iso 13485, Fda, CVAT, Labelbox, medical imaging software, annotation software tools, regulatory considerations in medical data handling
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