About this role
About Arctic Engine:
Arctic Engines is an enterprise-grade Al human data operations company specializing in high-quality training data, RLHF, and human feedback pipelines for frontier Al models. We are part of the Apna Group, one of India's fastest-growing unicorns, backed by marquee investors such as Lightspeed, Tiger Global, Insight Partners, Peak XV, and others. With native access to Apna's 60M+ workforce, we deliver high-quality training data at unmatched scale and speed.
Role: Video Annotator – Physical AI
Requirement: 50+
Company: Arctic Engines
Location: Remote | Freelancer
Experience: 1+ year in Physical AI or robotics video annotation
Joining: Immediate joiners preferred
Compensation : Rs 750/video hour
About the role
We are hiring Video Annotators to create accurate, timestamped annotations for egocentric videos captured in industrial and commercial environments. Candidates must have hands-on experience working on Physical AI datasets .
Requirements
Key responsibilities
- Review and annotate first-person video showing human actions, tools, objects, and task workflows.
- Split videos into meaningful chunks and mark precise start and end times for each action.
- Apply action labels and write clear natural language descriptions of what happens in each segment.
- Review model-generated annotations, correct errors, and ensure complete coverage and consistent labeling.
- Follow annotation guidelines, resolve unclear cases with reviewers, and complete rework within assigned timelines.
Required skills:
- Prior hands-on experience annotating Physical AI, robotics, or industrial egocentric video is mandatory.
- Understanding of temporal action segmentation, video chunking, action labeling, and timestamp accuracy.
- Ability to describe visible actions clearly, including the relevant hand, object, and tool.
- Experience with video annotation platforms
- Strong attention to detail and ability to meet quality and productivity targets.
Note: Apply through this platform with your CV and a brief description of the Physical AI annotation projects you have worked on.