Video Annotator - Physical AI
J
JobgetherPhysical AI, robotics
Fully remote freelance opportunity available across India.ContractJunior
Salary75,000,000 INR per year
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Job Details
- Experience
- 1+ year of hands-on experience working with Physical AI, robotics, or industrial egocentric video annotation.
Requirements
- Have 1+ year of hands-on experience with Physical AI, robotics, or industrial egocentric video annotation.
- Have prior experience annotating Physical AI datasets; this is mandatory.
- Understand temporal action segmentation, video chunking, action labeling, and timestamp precision.
- Accurately describe visible actions, including interactions involving hands, tools, objects, and equipment.
- Have experience using video annotation platforms or comparable data-labeling tools.
- Demonstrate attention to detail and strong visual observation skills.
- Follow detailed annotation guidelines and apply them consistently.
- Work independently in a remote environment and meet quality and productivity expectations.
- Be available for freelance work; immediate availability is preferred.
- Be prepared to provide a brief description of previous Physical AI annotation projects.
Responsibilities
- Review first-person and egocentric videos depicting human activities, tools, objects, and workflows in industrial or commercial environments.
- Divide videos into meaningful action segments and accurately identify each action's start and end timestamp.
- Apply appropriate action labels and write concise descriptions that reflect what is visible.
- Identify relevant hands, objects, tools, and interactions within each video segment.
- Review model-generated annotations, correct inaccuracies, and ensure complete and consistent coverage.
- Follow annotation guidelines and maintain consistent labeling standards across datasets.
- Identify and escalate ambiguous cases to reviewers when the correct annotation is unclear.
- Complete requested rework accurately and within assigned timelines.
- Meet quality, accuracy, and productivity targets while working independently.
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