Description review

Video Data Annotator

iMerit Technology · Remote · back to the listing

HR standards

72/100

solid

Title ↔ description

94/100

strong

Reads as

Unclear

no confident match

What the listing never says

  • No pay range published. Candidates cannot tell whether applying is worth their time. Pay transparency

The listing, marked up

Nothing in the wording of this listing tripped a check. The scores above still judge how complete and coherent it is.

Location: Remote

Engagement: Independent Contractor | Project-Based
iMerit, an EXL company, is looking for Video Data Annotators to support an AI training project.
You’ll review video footage and annotate actions, objects, and events according to detailed project guidelines. No prior AI experience is required.

Responsibilities

• Review and annotate videos.

• Identify and label actions, objects, and events accurately.

• Follow project guidelines and scoring criteria.

• Meet quality and productivity requirements.

• Flag unclear cases and provide feedback to the project team.

Requirements

• Excellent attention to detail.

• Ability to follow detailed guidelines consistently.

• Strong written communication skills.

• Comfortable working independently.

• Previous annotation, QA, or video evaluation experience is a plus.

• AI experience is not required.

Why Join?

• 100% remote project-based work.

• Work as an independent contractor.

• Contribute directly to the development of next-generation AI.

• Flexible project work, subject to project requirements and available assignments.

Please mention the word **IMPROVES** and tag RMmEwMjo0NzgwOjI4OmJhMTQ6OjE= when applying to show you read the job post completely (#RMmEwMjo0NzgwOjI4OmJhMTQ6OjE=). This is a beta feature to avoid spam applicants. Companies can search these words to find applicants that read this and see they're human.

How this was produced

Highlights are found by rule, not by a model: each one is a phrase matched at a known position, and every note is a template we wrote. The two scores come from a typed-decision model (Jev) that reads the listing against the official role definition and real listings for the same role, and returns probabilities rather than prose — it never writes any of the words on this page, and never chooses what to highlight.

Deterministic penalty applied to the HR score: 4 points (from 76 before penalties). Reviewed 25 Sep 2026.