About OpenTrain
OpenTrain is the #1 platform for people building careers in AI training and data labeling. We connect contributors with projects that help shape how modern AI systems behave and grow opportunities for long-term, flexible work.
For this project OpenTrain AI is the hiring and contracting organization. Creating an OpenTrain account is free and is how teams submit applications and manage contracts.
About AI training and data collection
AI training (also called data labeling or data collection) is the human work behind every modern AI system: people create and curate the examples models learn from. Collecting high-quality, diverse images is essential to building fair, accurate computer-vision systems.
Many contributors work part-time and on flexible schedules. Projects range from entry-level tasks to specialized field collection; this role focuses on local, offline image collection handled by in-person teams.
- Work directly shapes how AI models perform on real-world images.
- Great for teams that can run controlled, on-the-ground data collection in their local area.
The role
We are hiring local, on-the-ground teams to collect facial image data in their communities. This is contract, part-time work with pay of $25–30 USD per hour and an expected commitment of less than 20 hours per week.
Projects require coordination and field execution by teams based in the target local area; OpenTrain AI will contract directly with the selected teams.
- Pay: $25–30 USD per hour (PAY_PER_HOUR).
- Time: Less than 20 hours per week.
- Employment types: Contractor, Part-time.
- Data type: IMAGE; Label type: DATA_COLLECTION.
What you'll do
Run in-person facial image collection sessions in your local area following provided instructions and quality protocols. Work is offline and field-based — teams operate where participants and scenes are located, not remotely.
Maintain consistent quality across demographic groups and lighting conditions and follow strict quality-control requirements supplied by OpenTrain AI.
- Collect facial images across diverse demographics as specified.
- Capture data in varied lighting and environmental conditions while meeting quality standards.
- Operate as a coordinated local team to complete assigned collection tasks.
Requirements
Candidates must be established local teams with proven experience executing offline facial data collection projects. Basic English proficiency is required to follow instructions and coordinate with OpenTrain AI.
Because the work is field-based, teams must be based in the project’s local area and able to meet scheduling and quality demands within the stated weekly time commitment.
- Local team based in the target area (onsite/offline collection).
- Proven experience with on-the-ground facial data collection projects.
- Basic English proficiency.
- Ability to handle diverse demographics and varied lighting conditions.
- Available for less than 20 hours per week and able to contract as a part-time contractor.
Who should apply
Apply if your team has hands-on experience collecting facial images in your local community and you can demonstrate quality control practices. Entry-level contributors within an established team are welcome, but teams must show prior offline collection work.
This role is ideal for local teams that already run community outreach, field research, or in-person data collection operations and want short, flexible contracts.
- Local field teams with prior facial image collection experience.
- Groups that can maintain high quality across demographics and lighting.
- Teams comfortable communicating in basic English.
How to apply
Create an OpenTrain account and submit your team application describing your local experience, sample project details, hourly rate expectations, and availability. OpenTrain AI will review submissions and contact qualified teams with next steps.
Do not include sensitive personal data in your initial application; follow any submission instructions provided in the OpenTrain application flow.
- Sign up on OpenTrain and complete the team application.
- Provide examples of past offline facial data collection work and availability.
- Qualified teams will be contacted for vetting and contracting.
