Video Annotator - Physical AI

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.