Remote AI Training Document Annotator

Alignerr Corp.; United States; Remote; USD 17,000 - 30,000; Part time

Benefits offered by this job

Fully remote

Flexible hours

Ongoing project opportunities

Job summary

Alignerr is hiring a Document Review Specialist (AI Training) to read, annotate, and classify real-world documents from articles to technical reports. You will work remotely, with flexible hours between 10 and 40 per week, and collaborate asynchronously while maintaining strict accuracy and consistency.

The role emphasizes following detailed guidelines, extracting key information, and identifying entities and dates across diverse document types, all in English.

Qualifications

• Strong reading comprehension and ability to process diverse document types.
• Detail-oriented with a systematic, methodical approach.
• Comfortable following structured guidelines and applying them consistently.
• Self-motivated and reliable when working independently.
• Strong written communication in English.
• No legal, academic, or document management background required.

Responsibilities

• Read and annotate a wide variety of documents — articles, reports, forms, and more.
• Classify document sections, extract key information, and label important data points.
• Identify entities, dates, relationships, and structures within text.
• Follow detailed annotation guidelines with precision and consistency.
• Maintain a high standard of accuracy across large document sets.
• Work independently and asynchronously on your own schedule.

Skills

Reading comprehension

Attention to detail

Guideline adherence

Independent work

English writing

Tools

Annotation tools

Job description

Alignerr is hiring a Document Review Specialist (AI Training) to read, annotate, and classify real-world documents from articles to technical reports. You will work remotely, with flexible hours between 10 and 40 per week, and collaborate asynchronously while maintaining strict accuracy and consistency.

The role emphasizes following detailed guidelines, extracting key information, and identifying entities and dates across diverse document types, all in English.