Video Annotation AI Trainer, Remote Part-Time

About OpenTrain AI

OpenTrain AI is the #1 platform for finding and building careers in AI training and data labeling. We help freelancers discover projects, consolidate proof of work, and grow a durable portfolio that shows real experience working to teach AI.

Working with OpenTrain means joining the human side of AI development: annotators, reviewers, and trainers who help shape how machine learning systems learn from examples.

Why AI Training Work Matters

AI training (aka data labeling or annotation) is essential to modern AI: people produce the clean, labeled examples models learn from. This work is remote, flexible, and accessible—many projects require no prior experience beyond care and clear communication.

Contributors directly influence model behavior and quality while building portable, verifiable experience you can show on your OpenTrain profile.

The Role

As a Video Annotation AI Trainer you will annotate short video clips to produce high-quality training data. Your primary tasks include watching clips, marking events or frames with precise timestamps, and ensuring annotations meet project guidelines.

This is a remote, contract, part-time role requiring steady throughput and accuracy. Work is repetitive by design and coordinated with reviewers to keep labels consistent across large datasets.

• Data type: video clips for model training and evaluation.
• Labeling focus: event/frame timestamping, evaluation ratings, and data collection tasks.
• Employment: contractor, part-time; worldwide applicants accepted (English required).

What You'll Do Day to Day

You will follow clear annotation instructions to produce consistent, timestamped labels and perform accuracy checks on your own work before submission.

• Annotate short video clips according to project objectives and guidelines.
• Apply precise timestamps to events or frames of interest.
• Review and verify your own submissions for accuracy and completeness.
• Work at scale across repetitive video tasks while maintaining consistency.
• Coordinate remotely with reviewers to clarify ambiguous cases and ensure quality.

Requirements

Candidates must be comfortable with detailed written instructions and repetitive labeling work. Prior experience with video annotation tools is helpful but not strictly required for entry-level contributors.

• Strong English reading comprehension for following detailed written instructions.
• High attention to detail and consistency in annotation.
• Comfort with repetitive, high-volume video annotation tasks.
• Ability to perform accuracy checks on submitted annotations.
• Familiarity with video annotation tools or related labeling workflows is preferred.
• Good written and verbal communication for remote collaboration.

Schedule, Pay, and Commitment

This role is part-time and contractor-based with a minimum expected commitment of 20+ hours per week. Pay is hourly and ranges from $40 to $80 per hour depending on task complexity and reviewer feedback.

• Time requirement: 20+ hours per week (part-time contractor).
• Pay: hourly, $40–$80 per hour (PAY_PER_HOUR).
• Work location: fully remote, open to worldwide applicants who meet language requirements.

Who Should Apply

This role is well suited to entry-level applicants and seasoned annotators who enjoy detail-oriented, repetitive tasks and want to build a portfolio in AI training. It's a good fit for people seeking flexible remote work that can scale into broader opportunities.

• Entry-level annotators seeking paid, remote work in AI training.
• People with prior moderation, QA, or annotation experience who want to specialize in video.
• Freelancers building a trackable portfolio and reputation on OpenTrain.

How It Works

Apply and work through your OpenTrain AI account. You'll receive project instructions, annotate clips using the project's tools and interfaces, and submit work for reviewer feedback. Consistent, accurate contributors build stronger profiles and access to more projects over time.

• Create or use your OpenTrain account to apply and manage work.
• Follow project guidelines and submit timestamped annotations for review.
• Receive feedback from reviewers and incorporate corrections for consistent output.
• Build verifiable proof of work on your OpenTrain profile to access future projects.