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Senior Specialist Remote Data Annotation Jobs (NOW HIRING)

Senior Specialist, Marketing

Dallas, TX ยท Remote

$71K - $93K/yr

Hi, we're Oscar. We're hiring a Senior Specialist, Marketing to join our Marketing team. Oscar is the first health insurance company built around a full stack technology platform and a relentless

Senior Specialist, Marketing

Atlanta, GA ยท Remote

$71K - $93K/yr

Hi, we're Oscar. We're hiring a Senior Specialist, Marketing to join our Marketing team. Oscar is the first health insurance company built around a full stack technology platform and a relentless

Project Overview We are currently hiring AI/ML Data Contributors to support a range of active and upcoming projects across the United States. In this role, you will participate in tasks that help

Project Overview We are currently hiring AI/ML Data Contributors to support a range of active and upcoming projects across the United States. In this role, you will participate in tasks that help

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Senior Specialist Remote Data Annotation information

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$32

$63

How much do senior specialist remote data annotation jobs pay per hour?

As of Jun 12, 2026, the average hourly pay for senior specialist remote data annotation in the United States is $32.20, according to ZipRecruiter salary data. Most workers in this role earn between $21.15 and $39.42 per hour, depending on experience, location, and employer.

What is the difference between Senior Specialist Remote Data Annotation vs Data Labeler?

AspectSenior Specialist Remote Data AnnotationData Labeler
CredentialsHigh school diploma or equivalent; experience in data annotation; familiarity with annotation toolsHigh school diploma or equivalent; basic computer skills
Work EnvironmentRemote, often part of a team, with project deadlinesRemote or on-site, often individual tasks
Industry UsageUsed in AI/ML development across tech, automotive, healthcareUsed in AI/ML training datasets, often entry-level
Search/Comparison IntentUnderstanding roles with similar responsibilities and experience levelsClarifying entry-level data annotation roles

The Senior Specialist Remote Data Annotation role involves more experience, higher responsibility, and often oversight of annotation projects, whereas Data Labeler positions are typically entry-level with basic annotation tasks. Both roles are essential in AI/ML data preparation but differ in complexity and scope.

More about Senior Specialist Remote Data Annotation jobs
What cities are hiring for Senior Specialist Remote Data Annotation jobs? Cities with the most Senior Specialist Remote Data Annotation job openings:
What states have the most Senior Specialist Remote Data Annotation jobs? States with the most job openings for Senior Specialist Remote Data Annotation jobs include:
Infographic showing various Senior Specialist Remote Data Annotation job openings in the United States as of June 2026, with employment types broken down into 60% Full Time, 32% Part Time, 1% Temporary, and 7% Contract. Highlights an 87% Physical, 5% Hybrid, and 8% Remote job distribution, with an average salary of $66,986 per year, or $32.2 per hour.

Remote | AI Data Quality Review Expert -- $60-$80/hour

24-MAG

New York, NY โ€ข Remote

$60 - $80/hr

Part-time, Contractor

Posted 15 days ago


Job description

We are sharing a specialised part-time consulting opportunity for professionals experienced in AI data evaluation, structured review, annotation, quality control, rubric-based assessment, and high-accuracy human data workflows.

This role supports current and upcoming remote consulting opportunities focused on AI output review, structured data annotation, quality assessment, guideline-based evaluation, feedback documentation, and high-accuracy project execution. Selected professionals will apply strong attention to detail and structured reasoning to review AI outputs, identify subtle issues, follow complex guidelines, and support reliable data quality workflows.

Key Responsibilities

Professionals in this role may contribute to:

AI Output Review & Annotation

  • Review, evaluate, and annotate AI-generated outputs according to detailed project guidelines
  • Apply structured criteria consistently across repetitive and high-volume review tasks
  • Identify subtle errors, inconsistencies, edge cases, ambiguity, and quality issues
  • Support accurate human data workflows used to train and evaluate advanced AI systems

Guideline-Based Evaluation & Quality Control

  • Follow complex instructions carefully and apply nuanced rules with consistency
  • Review outputs for accuracy, completeness, clarity, reasoning quality, and alignment with task requirements
  • Flag unclear instructions, ambiguous cases, and recurring quality patterns
  • Maintain high accuracy across detail-heavy evaluation and labelling workflows

Structured Feedback & Review Documentation

  • Provide clear, concise, and structured feedback to improve downstream data quality
  • Document review decisions, issue patterns, and quality observations according to project standards
  • Support calibration workflows by applying rubrics and quality bars consistently
  • Maintain reliability, focus, and professional judgment across submitted work

Ideal Profile

Strong candidates may have:

  • Prior experience in AI data annotation, human data review, AI output evaluation, QA, structured review, rating, or rubric-based assessment
  • Strong attention to detail and ability to catch small inconsistencies, edge cases, and subtle quality issues
  • Ability to follow nuanced instructions precisely and apply them consistently
  • Strong written communication and reasoning skills
  • High reliability and comfort working independently on repetitive precision-based tasks
  • Quality-focused mindset and ability to maintain accuracy across long task batches

Educational Background

  • A degree or professional background in communications, writing, business, humanities, social sciences, computer science, data analysis, education, quality assurance, or a related field is helpful
  • Equivalent practical experience in annotation, review, QA, trust and safety, data evaluation, operations support, editing, or structured assessment work is also highly relevant

Nice to Have

  • Experience with large-scale AI data annotation, model evaluation, human feedback workflows, or data quality programs
  • Background in QA, structured review, trust and safety, content evaluation, editing, data labelling, or human data pipelines
  • Familiarity with multi-step rubric-based evaluation, calibrated feedback, guideline interpretation, or quality-control workflows
  • Experience documenting edge cases, recurring issues, quality patterns, or review decisions
  • Strong comfort working in detail-heavy, guideline-based, and accuracy-focused project environments

Why This Opportunity

  • Apply strong review judgment and attention to detail to structured remote project work
  • Contribute to high-quality AI data evaluation, annotation, and quality-control workflows
  • Work on flexible assignments aligned with your review, QA, or data evaluation background
  • Use your precision and reasoning skills in a focused, quality-first review environment
  • Remote structure with competitive hourly compensation

Contract Details

  • Independent contractor role
  • Fully remote with flexible scheduling
  • Part-time commitment depending on project availability
  • Competitive rates between $60โ€“$80 per hour depending on expertise
  • Weekly payments via Stripe or Wise
  • Projects may be extended, shortened, or adjusted depending on scope and performance
  • Work will not involve access to confidential or proprietary information from any employer, client, or institution

About the Platform

This opportunity is available through 24-MAG LLC. We connect experienced professionals with remote consulting opportunities across technical, evaluation, and project-based workstreams.

By submitting this application, you acknowledge that your information may be processed by 24-MAG LLC for recruitment and opportunity matching in accordance with our Privacy Policy: https://www.24-mag.com/privacy-policy.