$10–30/hr · micro1
Hands-on operator collecting high-quality robotic training data through precise manipulation tasks and meticulous protocol adherence.
What you would do
- Operate a handheld robotic gripper device to perform object picking, container opening, and household manipulation tasks
- Follow written task protocols with exactness to ensure consistent, high-quality data collection
- Restore physical environments after each attempt and check data quality before submission
- Detect and clearly communicate hardware issues, instruction ambiguities, or recording problems
Who they want
- Demonstrated fine motor skills, dexterity, and precision object handling ability
- Track record of reliability, punctuality, and personal accountability
- Comfort with repetitive physical tasks and stamina for extended work sessions
- Strong attention to detail and ability to follow complex instructions without deviation
- Quick ability to learn hardware interfaces and report technical issues clearly
Main skills
What the interview asks about
1.Precision task execution under observation
Data quality for AI training depends on exact task execution without skipping steps or taking shortcuts.
For example: “You're performing a sequence where you pick up an object, open a container, place it inside, and close the container. A step is unclear in the instructions. Describe how you'd handle this.”
2.Physical environment reset and verification
Inconsistent setup between attempts corrupts training data and forces the team to discard entire collections.
For example: “After 50 task completions, you notice the test environment gradually changing from its initial state. How would you identify what needs resetting each cycle?”
3.Hardware issue detection and reporting
Silent hardware failures produce corrupted data that can go unnoticed for hours, wasting expensive compute resources.
For example: “Midway through a task session, the gripper occasionally fails to grip objects fully. What would you check before reporting this to the project lead?”
4.Attention to detail in complex sequences
Even small deviations in hand position or movement speed can render hours of collected data unusable for model training.
For example: “You've completed 30 identical manipulation tasks, but on task 31 you notice the recording looks slightly different. What would you do?”
5.Endurance and consistency over extended sessions
Data quality degrades significantly when operators fatigue, introducing unwanted variability into training datasets.
For example: “You've been performing repetitive tasks for 6 hours straight and feel your focus slipping. How would you ensure you don't compromise data quality?”
A task you may get
Perform a simulated sequence of precise object manipulation tasks following detailed written instructions, demonstrating protocol adherence and identifying process improvements.
How to prepare
- Practice fine motor control and precision hand movements with small objects
- Study systematic approaches to following multi-step instructions exactly
- Review common hardware failures and troubleshooting communication practices
- Build physical and mental endurance for sustained repetitive work
The facts
- Pay
- $10–30/hr
- 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
- Generalist
- Posted
- 9/10/2026
- Places left
- 10
We wrote this page from the public micro1 listing. It may be out of date, so read the full posting before you apply.