Editor (Remote)

Quik Hire Staffing; United States; Remote; USD 25,000 - 39,000; Full time

Job summary

Quik Hire Staffing is seeking a detail-oriented Data Labeling Specialist to review, annotate, and structure multimodal datasets for AI models. This remote role supports applicants in the United States and Canada, working with text, images, spreadsheets, and complex documents.

You will ensure data quality by following project guidelines, reviewing model outputs for accuracy and coherence, and flagging ambiguities to improve labeling taxonomies.

Qualifications

• Exceptional attention to detail, reading comprehension, and analytical evaluation skills.
• Prior experience in data annotation, quality assurance, data review, or content evaluation is preferred.
• Native or professional-level English proficiency (written and verbal).

Responsibilities

• Annotate, categorize, and validate large-scale multimodal datasets according to project guidelines.
• Review AI model outputs for factual accuracy, linguistic coherence, alignment, and formatting correctness.
• Identify edge cases, labeling ambiguities, and data inconsistencies to help improve labeling taxonomies.
• Maintain high accuracy, quality benchmarks, and daily throughput goals.

Skills

Attention to detail

Reading comprehension

Analytical evaluation

Job description

• Location: Remote (United States & Canada Only)

Employment Type: Contract / Full-Time

Important Eligibility Notice

Location: Applications are strictly restricted to individuals currently residing in and authorized to work in the United States or Canada. Submissions from other regions will be automatically filtered out.

Overview

We are looking for a detail-oriented Data Labeling Specialist to review, annotate, and structure multimodal datasets for advanced artificial intelligence models. You will play a crucial role in improving data quality across text, images, spreadsheets, and complex structured documents.

Key Responsibilities

• Annotate, categorize, and validate large-scale multimodal datasets according to strict project guidelines.
• Review AI model outputs for factual accuracy, linguistic coherence, alignment, and formatting correctness.
• Identify edge cases, labeling ambiguities, and data inconsistencies to help improve labeling taxonomies.
• Maintain high accuracy, quality benchmarks, and daily throughput goals.

Requirements

• Exceptional attention to detail, reading comprehension, and analytical evaluation skills.
• Prior experience in data annotation, quality assurance, data review, or content evaluation is preferred.
• Native or professional-level English proficiency (written and verbal).
• Reliable high-speed internet and home office setup.
• Must be currently based in the United States or Canada.

Equal Opportunity Employer

We are an equal opportunity employer. We are committed to building an inclusive workplace and welcome applications from all qualified individuals regardless of race, color, ethnicity, nationality, gender, gender identity or expression, sexual orientation, age, religion, disability, marital status, or any other characteristic protected by applicable law. All hiring decisions are made solely on the basis of qualifications, skills, and demonstrated ability.