Odia Document Annotation Specialist

Mercor; Greater London; On-site; GBP 24,000 - 34,000; Full time

Benefits offered by this job

Regional-language AI data experience

Transcription & localization support

Document production workflow

Job summary

Mercor seeks a native Odia speaker to annotate and transcribe Odia documents with precision. You will identify and bound page regions, assign types, and ensure correct reading order, handling complex layouts and handwriting.

Responsibilities include sourcing Odia PDFs, recording metadata, and ensuring accurate, line-by-line transcription in Odia. The role emphasizes quality control with second-expert reviews and meticulous documentation of every page component.

Qualifications

• Native Odia speaker with full command of Odia script and diacritics.
• Experience in annotation, transcription, translation, localization, subtitling, proofreading or regional-language data review.
• Exactness is crucial; character-level accuracy matters over speed.
• Systematic applicant applies taxonomy consistently across pages.
• Comfort with unfamiliar layouts like multi-column newspapers and handwritten forms.

Responsibilities

• Source publicly accessible Odia PDFs with multimodal elements and record source.
• Annotate structure: bound every meaningful region and assign type and reading order.
• Record relationships by linking regions to parent figures/tables.
• Transcribe faithfully in Odia, flag illegible regions clearly.
• Capture page metadata: language, document type, source, dimensions, and flags for special content.
• Review a colleague's work through second-expert review.

Skills

Native Odia speaker

Document annotation experience

Character-level accuracy

Systematic work approach

Adaptable to multi-column layouts

Job description

Fluent Language Skills Required:

Odia. Native fluency in Odia (Oriya), including full command of Odia script and orthography, is required for this position. All annotation and transcription work is performed in Odia.

Why This Role Exists

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: Odia, 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 Odia 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.

What You'll Do

• Source documents: find a publicly accessible Odia PDF in an assigned document type, containing at least one multimodal element (images, tables, diagrams, or handwriting), and record where you obtained it

• Annotate 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

• Record relationships: link each region to the figure or table it belongs to through a parent component identifier

• Transcribe faithfully: reproduce all text exactly as it appears in Odia script, including handwritten content, flagging any region where the source is not legible

• Capture page metadata: language, document type, source, page dimensions, and flags for tables, formulas and handwriting

• Review a colleague's work: every task is reviewed end to end by a second Odia expert, and experienced annotators take on that review

Who You Are

• You are a native Odia speaker with full command of the script, its diacritics and its conjunct forms

• You have worked with documents: annotation, transcription, translation, localization, subtitling, proofreading, journalism, or regional-language data review

• You are exact: character-level accuracy matters more here than speed, and a single wrong diacritic is a defect

• You are systematic: you apply a taxonomy consistently across hundreds of pages rather than improvising per document

• You are comfortable with unfamiliar layouts: multi-column newspapers, exam papers, handwritten forms

Nice-to-Have Specialties

• Regional-language AI data: annotation, labeling, grading, or bilingual evaluation for training datasets

• Transcription and localization: MTPE, subtitling, bilingual QA, OCR correction or post-editing

• Document production: typesetting, copy-editing, proofreading, or digitization of Odia-language material

• Script and encoding: Unicode normalization, Odia input methods, numeral-form and character-form accuracy

What Success Looks Like

• Every meaningful region on the page is captured, correctly bounded and correctly typed

• Reading order reflects how the page is actually read, including across columns

• Transcriptions match the source character for character, in Odia script rather than transliteration

• Your tasks pass second-expert review the first time

• The documents you bring in add layout diversity rather than repeating templates already in the corpus

Why Join Mercor

• Build the training data that makes document AI work in scripts it currently handles badly

• Work from real published Odia documents rather than synthetic or templated pages

• Quality leads on this project: accuracy is the first measure, with handling time tracked alongside it