Odia Document Annotation Specialist

ppbFluent Language Skills Required: /b Odiya. Native fluency in Odiya (Oriya), including full command of Odiya script and orthography, is required for this position. All annotation and transcription work is performed in Odiya. /ph3Why This Role Exists /h3pDocument understanding breaks down fastest in the languages that parsing and vision-language models rarely see. This project builds training data for exactly those languages: Odiya, 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. /ppThe 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 Odiya documents rather than a narrow band of easily parsed ones. /ppDelivered work is human-authored throughout. Component identification, component typing, reading order and all transcription are performed by people, not generated by parsing models. /ph3What You'll Do /h3ullipOpen and check a task: pages are provided, so you do not source documents yourself. We find the PDFs and upload them for you. Before annotating, confirm the page is in Odiya, is legible, has real content, and shows no personal details /p /lilipAnnotate structure: identify and bound every meaningful region of the page - document title, section heading, paragraph, list, table, figure, diagram, caption, formula, question, answer field - and assign each a component type and a reading-order index /p /lilipRecord relationships: link each region to the figure or table it belongs to through a parent component identifier /p /lilipTranscribe faithfully: reproduce all text exactly as it appears in Odiya script, including handwritten content, flagging any region where the source is not legible /p /lilipCapture page metadata: language, document type, source, page dimensions, and flags for tables, formulas and handwriting /p /lilipReview a colleague's work: every task is reviewed end to end by a second Odiya expert, and experienced annotators take on that review /p /li /ulh3Who You Are /h3ullipYou are a native Odiya speaker with full command of the script, its diacritics and its conjunct forms /p /lilipYou have worked with documents: annotation, transcription, translation, localization, subtitling, proofreading, journalism, or regional-language data review /p /lilipYou are exact: character-level accuracy matters more here than speed, and a single wrong diacritic is a defect /p /lilipYou are systematic: you apply a taxonomy consistently across hundreds of pages rather than improvising per document /p /lilipYou are comfortable with unfamiliar layouts: multi-column newspapers, exam papers, handwritten forms /p /li /ulh3Nice-to-Have Specialties /h3ullipRegional-language AI data: annotation, labeling, grading, or bilingual evaluation for training datasets /p /lilipTranscription and localization: MTPE, subtitling, bilingual QA, OCR correction or post-editing /p /lilipDocument production: typesetting, copy-editing, proofreading, or digitization of Odiya-language material /p /lilipScript and encoding: Unicode normalization, Odiya input methods, numeral-form and character-form accuracy /p /li /ulh3What Success Looks Like /h3ullipEvery meaningful region on the page is captured, correctly bounded and correctly typed /p /lilipReading order reflects how the page is actually read, including across columns /p /lilipTranscriptions match the source character for character, in Odiya script rather than transliteration /p /lilipYour tasks pass second-expert review the first time /p /lilipUnsuitable pages are flagged up front rather than after thirty minutes of work /p /li /ulh3Why Join Mercor /h3ullipBuild the training data that makes document AI work in scripts it currently handles badly /p /lilipWork from real published Odiya documents rather than synthetic or templated pages /p /lilipQuality leads on this project: accuracy is the first measure, with handling time tracked alongside it /p /li /ul /p #J-18808-Ljbffr