Gujarati PDF Annotation Specialist

Obsidian; Dublin; On-site; EUR 17,000 - 25,000; Full time

Job summary

Mercor is seeking a meticulous Gujarati annotator to map and transcribe Gujarati documents with full script accuracy. You will identify and bound sections such as titles, headings, paragraphs, and figures, assign types and reading order, and ensure precise transcription down to handwritten content.

The role emphasizes strict quality controls and two-person review to maintain high accuracy across diverse layouts and scripts, including multi-column pages and diagrams.

Qualifications

• Native Gujarati speaker with full command of Gujarati script and orthography.
• Character-level accuracy is critical; exact transcription required.

Responsibilities

• Source publicly accessible Gujarati PDFs in assigned document type with multimodal elements.
• Annotate structure by bounding every meaningful region and assigning type and reading order index.
• Record relationships by linking regions to their parent figure or table.
• Transcribe faithfully in Gujarati script, flagging illegible regions.
• Capture page metadata: language, document type, source, dimensions, and flags for tables handwriting.
• Undergo second-expert review as part of a two-person verification process.

Skills

Gujarati fluency

Native Gujarati speaker

Attention to detail

Job description

Fluent Language Skills Required: Gujarati. Native fluency in Gujarati, including full command of Gujarati script and orthography, is required for this position. All annotation and transcription work is performed in Gujarati.

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: Gujarati, 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 Gujarati 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 Gujarati 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 Gujarati 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 Gujarati expert, and experienced annotators take on that review

Who You Are

• You are a native Gujarati 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 Gujarati-language material

• Script and encoding: Unicode normalization, Gujarati 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 Gujarati 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 Gujarati documents rather than synthetic or templated pages

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