micro1
You submit personal photographs with your twin to help train AI systems that recognize facial features and visual similarity.
What you would do
- Take photos of yourself and your twin using your smartphone
- Follow specific guidelines for angles, lighting, framing, and pose
- Verify each image meets resolution and file format requirements
- Complete demographic questionnaires about yourself and submitted images
Who they want
- 18+ years old with a twin sibling willing to participate
- Located in North America, Latin America, or Europe/Middle East/Africa/Asia
- Own a functioning smartphone and reliable internet connection
- Ability to follow detailed technical instructions precisely
Main skills
What the interview asks about
1.Interpreting visual specifications
Accurate data collection depends on your ability to understand and apply technical image requirements that are critical for model training.
For example: “A guideline states minimum 2.5 megapixel resolution and specifies three distinct angles: frontal, 45 degrees left, 45 degrees right. Your phone camera is 12 MP but the 45-degree shots look darker. Would you reframe, adjust lighting, or try another approach?”
2.Consistency across multiple sessions
Training data quality requires that images across different submission batches maintain similar lighting, background, and composition.
For example: “Your first submission batch has you photographed against a white wall in natural window light. Three weeks later, you're in a different room with overhead fluorescent light. How would you ensure consistency?”
3.Coordination and timing
Twin data is only useful when both siblings participate; understanding logistical constraints tests your project management capability.
For example: “Your twin is available only on weekends, but the project deadline is approaching. How would you balance schedule constraints with image quality and metadata accuracy?”
4.Quality control and self-rejection
Dataset integrity depends on contributors recognizing when their own work doesn't meet spec and withdrawing it rather than padding submission counts.
For example: “You've captured 20 frontal-facing photos. Reviewing them, 3 are slightly blurry, 2 have shadows across your face, and 15 meet spec. Do you submit all 20 or report only the qualified ones?”
How to prepare
- Test your smartphone camera in different lighting conditions to determine which settings produce images with sufficient pixel density and color accuracy
- Set up a dedicated space with consistent background, distance, and lighting that you can reproduce across multiple sessions
- Coordinate availability with your twin and establish a shared understanding of image guidelines so submissions are aligned
The facts
- Open to
- Bangladesh, Hong Kong, India, Indonesia, Japan, Kazakhstan, Kyrgyzstan, Malaysia, Pakistan, Philippines, Singapore, Sri Lanka, Taiwan, Thailand, Uzbekistan, Vietnam, Austria, Belarus, Belgium, Denmark, France, Germany, Greece, Italy, Netherlands, Portugal, Russia, Spain, Switzerland, United Kingdom, Argentina, Brazil, Chile, Colombia, Mexico, Peru, Algeria, Bahrain, Egypt, Iraq, Jordan, Kuwait, Lebanon, Libya, Morocco, Oman, Palestine, Qatar, Saudi Arabia, Tunisia, United Arab Emirates, United States, Canada, Nigeria, Kenya, South Africa, Ghana, Ethiopia
- Field
- Robotics
- Role type
- Expert
- Posted
- 9/14/2026
- Places left
- 5000
We wrote this page from the public micro1 listing. It may be out of date, so read the full posting before you apply.