Generative AI Data Analysts - Dogri

About the role

OVERVIEW

We are looking for Generative AI Analysts to support labeling and quality review across multimedia data (e.g., video, images, and related metadata). This role is best suited for candidates with several years of annotation and QA experience, strong attention to detail, and comfort working with structured guidelines at high volume.

MAIN DUTIES

Annotate and review multimedia data accurately using defined labeling rules (e.g., event tagging, temporal boundaries, object/entity attributes, consistency checks).
Follow detailed guidelines consistently; flag ambiguous cases and edge scenarios with clear examples for resolution.
Perform self-QA on completed work and correct errors before submission.
Participate in calibration sessions to align interpretation of guidelines and reduce reviewer-to-reviewer variance.
Track recurring issues and contribute to guideline improvements by documenting examples, failure modes, and recommended clarifications.
Support quality workflows (sampling, second-pass review, audits) and incorporate feedback into subsequent work.
Coordinate with internal stakeholders and external partners as needed to meet throughput and quality targets.

Project Details

Duration: Ongoing

Employment Type: Full time employee

Location: Remote

Language: Dogri

By applying, you'll become part of our community, opening doors to a range of projects tailored to your skills and availability.

Joining us means contributing to our current project and becoming part of our dynamic network.

This is a unique chance to enhance global user experiences and apply your language skills in meaningful ways.

Qualifications

3+ years of experience in multimedia annotation, multimodal data labeling, computer vision labeling, content QA, or a closely related field.
Demonstrated ability to maintain high accuracy and consistency across repetitive, detail-oriented work.
Strong written and verbal communication in Dogri (to document issues clearly and ask precise questions).
Comfortable working with multimedia content for extended periods while maintaining focus and accuracy.
Experience working from structured guidelines and meeting productivity/quality expectations.

About Remote

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