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Mercor is seeking a native Malayalam speaker for precise document annotation and transcription tasks. You will label page regions, ensure reading order, and transcribe Malayalam script with character-level accuracy.
This role emphasizes attention to detail and consistency across complex layouts, multi-column text, and handwritten content. The project focuses on creating training data for Malayalam and other Indic scripts; you will review work and adhere to strict quality standards, with remote
Fluent Language Skills Required: Malayalam. Native fluency in Malayalam, including full command of Malayalam script and orthography, is required for this position.
Document understanding breaks down fastest in the languages that parsing and vision-language models rarely see. This project builds training data for exactly those languages: Malayalam, alongside four other Indic scripts, Japanese and Korean. Each task takes a real, publicly available PDF page and produces a complete structural map of that page, paired with a faithful transcription of every text region in the original script.
The dataset deliberately concentrates on the material models handle worst: handwriting, dense multi-column layouts, tables, diagrams, and mixed-script pages. Documents are drawn from newspapers, textbooks, examinations, and everyday formats such as flyers, forms, manuals, menus, brochures, notices and worksheets, so that the corpus reflects the real diversity of Malayalam documents rather than a narrow band of easily parsed ones. Delivered work is human-authored throughout. Component identification, component typing, reading order and all transcription are performed by people, not generated by parsing models.
Build the training data that makes document AI work in scripts it currently handles badly. Work from real published Malayalam documents rather than synthetic or templated pages. Quality leads on this project: accuracy is the first measure, with handling time tracked alongside it.