Video Annotation Quality Reviewer

Help AI understand what is happening inside a video

OpenTrain AI is looking for a Video Annotation Quality Reviewer to check and improve the training data used to teach AI systems how to interpret human actions and movement.

Rather than creating content or training machine-learning models directly, you'll work on the human quality-control layer behind AI training: reviewing existing video annotations, finding mistakes and making precise corrections.

The opportunity is fully remote, open to candidates worldwide and pays $15–$20 per hour.

What does video annotation quality review involve?

Modern computer vision systems learn from large collections of labeled examples.

In video datasets, those labels might describe an action taking place in a sequence or capture information about the position of a person's hands. If those annotations are inaccurate, inconsistent or incomplete, the quality of the data used to train the AI suffers.

Your job is to catch those problems.

You'll compare annotations against the actual video content and established project guidelines, deciding whether each label accurately represents what's happening on screen.

What you'll be doing

Your responsibilities will include:

• Reviewing annotations across different video datasets.
• Checking action labels for accuracy and consistency.
• Identifying missing, incorrect or incomplete annotations.
• Assessing hand-pose data against defined quality standards.
• Reviewing English-language action descriptions.
• Correcting annotation errors precisely.
• Flagging discrepancies that require further attention.
• Documenting corrections and findings using standardized formats.
• Providing concise written feedback.
• Suggesting improvements when annotation guidelines create ambiguity or recurring quality problems.

The work requires consistency. Similar situations need to be evaluated using the same standards across potentially large datasets.

Attention to detail matters more than years of experience

This is listed as an entry-level opportunity, and previous professional experience in AI isn't required.

What matters more is your ability to work methodically and notice small discrepancies that other people might overlook.

You should be comfortable following detailed instructions, applying quality standards consistently and explaining why you've made a particular correction.

OpenTrain is looking for candidates with:

• Strong English reading and writing skills.
• Excellent attention to detail.
• A systematic approach to reviewing visual information.
• The ability to identify accuracy, consistency and completeness problems.
• Clear written communication.
• The ability to work independently and manage assigned deliverables.
• Comfort working with video annotation tools and larger datasets.

Experience that could help

Previous exposure to video annotation, data annotation or annotation quality assurance would be useful, although it isn't a requirement.

Knowledge of concepts related to action recognition or hand-pose analysis could also help you understand what the datasets are trying to capture and identify less obvious annotation problems.

The role could therefore be particularly interesting for someone who wants practical exposure to the processes behind computer vision and AI training without needing an established machine-learning career.

Build experience in the human side of AI

Much of the attention around artificial intelligence focuses on models and algorithms, but the quality of those systems also depends heavily on the examples humans prepare and evaluate.

This role provides an accessible entry point into that process.

Your work will help determine whether video training data is reliable enough for AI systems to learn from — giving you hands-on experience with data quality, annotation standards and AI evaluation workflows.

Over time, projects like this can also help build a portfolio of AI training experience demonstrating careful judgment, quality assurance and familiarity with structured data-review processes.

Contract details

This is a part-time independent contractor opportunity requiring at least 20 hours per week.

OpenTrain lists:

• $15–$20/hour
• 100% remote
• Worldwide eligibility
• 20+ hours per week
• English as the working language
• Entry-level experience

Candidates will need to create a free OpenTrain profile before applying.