Video Annotator - Physical AI
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About Arctic Engine:
Arctic Engines is an enterprise-grade AI human data operations company specializing in high-quality training data, RLHF, and human feedback pipelines for frontier AI 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 β Physical AI
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
- 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.
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.
Note: Apply through this platform with your CV and a brief description of the Physical AI annotation projects you have worked on.
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Apna is a premier, enterprise-grade professional networking and recruitment marketplace engineered to orchestrate massive-scale blue-collar and gray-collar labor ecosystems and intelligent, frictionless hiring workflows. Operating as a mobile-first, AI-driven digital hub, the company eliminates the operational friction of traditional, legacy-recruitment modelsβwhich frequently suffer from low engagement, opaque candidate vetting, and high administrative overheadβby seamlessly deploying advanced voice-enabled AI-calling telemetry, rigorous vernacular-matching architectures, and cohesive community-based professional-networking frameworks. Moving beyond rigid legacy job-board paradigms, Apna empowers over 55 million registered users and thousands of MSMEs and large enterprises to dynamically synchronize their talent-acquisition pipelines with elite, high-velocity autonomous execution. Under the hood, their sophisticated proprietary data infrastructureβnatively managing over 15 million interviews monthlyβhandles complex multi-vector profile ingestion, instantaneous AI-recommended lead routing, and automated candidate-assessment workflows, providing the necessary operational foundation to reduce time-to-hire by over 50%. What sets Apna apart is its uncompromising dedication to frictionless labor orchestration; by bridging the gap between highly volatile, localized informal labor markets and accessible, high-trust digital hiring environments, the platform empowers modern emerging-market workforces to radically accelerate their employment velocity, eliminate structural job-market bottlenecks, and build an unassailable foundation for continuous commercial and institutional dominance in the modern, AI-transformed global digital-hiring landscape.
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