Every AI system that can tell a cooking video from a combat video learned it from a person who made that call first. That person is you.

We're hiring a Multilingual Data Annotation Specialist to label video, image, and metadata content across YouTube, TikTok, Meta, and Snap, and to bring cultural fluency to calls that a model can't make on its own. A clip that reads as harmless in one market reads very differently in another. Catching that difference is the whole job.

Your labels become the ground truth our machine learning systems train on and get measured against. When you get a hard call right, the system gets better at it. When the guidelines don't cover the case in front of you, you're the one who tells us the guidelines need to change.

This role suits someone who finds ambiguity interesting rather than frustrating, who'd rather ask a sharp question than guess, and who takes real satisfaction in precision.

Here's what you'll get to do:

Label social media content against Zefr's contextual category guidelines using our in-house tooling.

Make daily judgment calls on video, image, and metadata — including content where cultural and linguistic context changes the answer.

Apply labeling frameworks, then help us sharpen them when you find the gaps.

Spot emerging trends and edge cases early, and raise them before they become systemic mislabels.

Run root cause analysis on quality misses and turn what you find into process changes.

Perform lingual quality assurance across multiple project pipelines.

You'll also build a working understanding of machine learning and computer vision, and of exactly how annotation quality shows up in model performance.

Multilingual Data Annotation Specialist, Hindi

Responsibilities

Qualification

Required

Preferred

Benefits

Company

Zefr

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