AI Training Document Annotator — Remote & Flexible Hours

Alignerr Corp.; Ciudad de México; Hybrid; MXN 207,000 - 317,000; Part time

Benefits offered by this job

Fully remote and flexible

Freelance autonomy

Opportunity for ongoing work and renew

Job summary

Alignerr is seeking a Document Review Specialist (AI Training) to read, annotate, and classify real-world documents from articles to financial reports. This fully remote, hourly contract role offers 10–40 hours per week and requires strong English proficiency, attention to detail, and the ability to work independently with structured guidelines.

You will annotate diverse documents, extract key information, label data points, and identify entities and dates while maintaining high accuracy across

Qualifications

• Strong reading comprehension and ability to process diverse document types.
• Detail-oriented and methodical in approach.
• Ability to follow structured guidelines consistently.
• Self-motivated and reliable when working independently.
• Strong written English communication.

Responsibilities

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

Skills

Reading comprehension

Detail-oriented

Structured guidelines

Self-motivated

Written English

Tools

Annotation tools

Job description

Alignerr is seeking a Document Review Specialist (AI Training) to read, annotate, and classify real-world documents from articles to financial reports. This fully remote, hourly contract role offers 10–40 hours per week and requires strong English proficiency, attention to detail, and the ability to work independently with structured guidelines.

You will annotate diverse documents, extract key information, label data points, and identify entities and dates while maintaining high accuracy across