English Text Annotation & Review (Argentina)

About OpenTrain

OpenTrain is the #1 platform for finding and building careers in AI training and data labeling. We connect people with meaningful work that helps train the next generation of AI systems and provide a place to grow skills, build a profile, and apply in minutes.

OpenTrain hires and contracts directly for this project. Joining gives you hands-on experience in the fast-growing field of AI training and an opportunity to contribute to high-impact datasets used for model development.

About AI Training Work

AI training (data labeling / annotation) is the human side of building AI: people create and validate the examples models learn from. This kind of work is often flexible and accessible, with many entry-level opportunities for people who are detail-oriented and reliable.

As a contributor you’ll directly influence how AI systems behave by producing consistent, high-quality labeled data.

• Work common in this industry: text classification, review, transcription, image/video labeling, and evaluation of model outputs.
• Typical advantages: flexible hours, remote-capable roles, and opportunities to learn annotation tools and QA workflows.

The Role

We are looking for Argentina-based freelancers to review English text that has been pre-annotated. You will verify whether existing classification tags are accurate and correct any missing or incorrect tags using an online labeling tool.

This is an entry-level, part-time contractor role (less than 20 hours per week). Accuracy, consistency, and on-time delivery matter—the labeled data you produce will be used for analysis and model training.

• Data type: English text.
• Label type: Classification (review and correct tags).
• Work arrangement: Contractor, part-time, under 20 hours/week.

What You'll Do

Your core task is to review pre-annotated English snippets and confirm or correct classification tags so they follow project guidelines. Use the provided online tool to apply edits and leave clear notes when items are ambiguous.

You will follow project instructions and examples to ensure consistency across the dataset and escalate unclear cases to the project team when necessary.

• Check pre-applied labels for accuracy and completeness.
• Add or correct classification tags according to guidelines.
• Use the online labeling tool to record changes and comments.
• Follow examples and written instructions to keep labels consistent.
• Report patterns or frequent errors to improve guidelines and QA.

Requirements

We will only consider candidates who meet the location and language requirements below and who demonstrate attention to detail and reliable communication.

• Must currently reside in Argentina.
• Minimum B2 English proficiency (CEFR) — strong reading comprehension required.
• Strong attention to detail and ability to meet deadlines consistently.
• Good written communication skills.
• Previous experience in data labeling or related tasks is preferred but not required.
• Familiarity with labeling/annotation tools is a plus; quick learners of new platforms welcome.

Interview & Test Questions

During the interview you will be asked to answer short multiple-choice classification questions to demonstrate reading comprehension and tagging judgment. Responses will be used to help score and qualify candidates.

Do not expect technical or domain-specific knowledge beyond understanding English text and basic classification choices.

• Question 1 - Snippet: “I can’t believe how expensive movie tickets have become. This is outrageous, and I won’t be going to the cinema anytime soon!” — Options: A. Personal Complaint | B. Product Advertisement | C. News Report
• Question 2 - Snippet: “Join us this Saturday for the grand opening of our new bakery in downtown Chicago! We’ll have free samples and great deals all day long.” — Options: A. Promotional Announcement | B. Travel Experience | C. Academic Summary
• Question 3 - Snippet: “Sarah completed her PhD in Computer Science last year. She now teaches at a local university and publishes research papers on machine learning.” — Options: A. Personal Complaint | B. Professional Biography | C. Consumer Review

Compensation, Schedule & How To Apply

This role pays USD 3.50 per hour and is billed on an hourly contractor basis. Expected workload is less than 20 hours per week, and schedules are part-time and flexible within project deadlines.

To apply, prepare a brief note describing any relevant labeling experience (if available), confirm you reside in Argentina, and state your CEFR English level. Successful applicants will receive project guidelines and access to the online labeling tool.

• Payment type: Hourly contractor — USD 3.50 / hour.
• Hours: Less than 20 hours per week, part-time and flexible.
• Employment types: Contractor, Part-time.
• Next steps: Apply with your location and English proficiency; expect a short qualification test during interview.