Video Data Annotation Intern

5 hours ago

Chandigarh, Chandigarh, India PaladinAi Full time ₹ 5,00,000 - ₹ 15,00,000 per year

Video Data Annotation Specialist – Forensic AnalysisLocation:RemoteDepartment:Data Ops TeamEmployment Type:Full-timeAbout the RoleWe are seeking an experiencedVideo Data Annotation Specialistwith strong expertise inforensic video analysisworkflows. The role involves detailed annotation and metadata tagging of sensitive forensic video datasets involving facial regions, actions, identities, tampering indicators, and other evidentiary details.The ideal candidate will have experience working withAI-driven video investigation projects, along with a strong command ofannotation tooling, QA processes, and data governance standards.Key ResponsibilitiesPerform frame-level and sequence-level annotation for forensic video datasets, including:Face and person trackingObject and vehicle labelingAction taggingScene change detection and event segmentationIdentify and tag tampering cues , such as missing frames, splices, or compression artifacts.Configure and manage annotation tools and pipelines (CVAT, Supervisely, V7, or internal forensic labeling systems).Maintain strict data confidentiality and chain-of-custody documentation .Define annotation guidelines specific to forensic evidence handling.Conduct quality audits and maintain >95% accuracy and inter-annotator consistency.Collaborate with forensic analysts and AI researchers to refine model training datasets.Generate summary reports of annotated findings for internal documentation and validation.RequirementsPrior exposure to forensic or investigative video datasets (law enforcement, cybercrime, or lab projects).Proficient in CVAT, Label Studio, Supervisely, V7 Darwin, or equivalent tools.Understanding of video formats, compression, metadata, and temporal labeling .Familiarity with forensic media standards (e.g., chain of custody, evidence preservation).Basic scripting knowledge in Python, OpenCV, or FFmpeg for preprocessing and frame extraction.Excellent attention to visual and temporal details; high data accuracy tolerance.Ability to work under confidentiality protocols and handle sensitive evidence.Preferred QualificationsExperience in face or gait analysis datasets , or deepfake/tampering detection annotation.Exposure to AI-based forensic tools or ML dataset preparation pipelines.Knowledge of image forensics metrics (e.g., PRNU, ELA, or compression-based indicators).

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