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Remote Data Annotator Jobs (NOW HIRING)

Mercor

Data Annotator

New York, NY · Remote

$50/hr

Remote Role Responsibilities * Review, evaluate, and annotate AI outputs with extreme attention to ... Prior experience as a CB / reviewer / rater in human data or AI training pipelines . * Proven ...

RWS TrainAI

Language Data Annotator (US)

Dallas, TX · On-site +1

... remote work? Are you interested in shaping the development and safety of today's AI models? What ... AI & Data Capabilities (Preferred): Experience in one or more of the following areas: machine ...

RWS TrainAI

Language Data Annotator (US)

Dallas, TX · On-site +1

... remote work? Are you interested in shaping the development and safety of today's AI models? What ... AI & Data Capabilities (Preferred): Experience in one or more of the following areas: machine ...

The University of Pennsylvania

Linguistic Annotator

$7.25 - $17/hr

The Linguistic Annotator will work on transcribing and annotating audio recordings for use in ... data in a social/behavioral research setting * Other duties as assigned This is a fully remote ...

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How much do remote data annotator jobs pay per year?

As of Jun 7, 2026, the average yearly pay for remote data annotator in the United States is $165,018.00, according to ZipRecruiter salary data. Most workers in this role earn between $133,500.00 and $170,000.00 per year, depending on experience, location, and employer.

What is a Remote Data Annotator?

A Remote Data Annotator is a professional who labels, categorizes, or tags data—such as images, text, audio, or video—while working from a remote location. This annotated data is then used to train and improve machine learning models and artificial intelligence systems. Data annotators ensure the quality and accuracy of data, which is crucial for AI applications like self-driving cars, voice recognition, and search engines. The work can vary from simple labeling tasks to more complex categorization, depending on the project requirements.

What are the key skills and qualifications needed to thrive as a Remote Data Annotator, and why are they important?

To thrive as a Remote Data Annotator, you need strong attention to detail, accuracy, and a basic understanding of data labeling concepts, often supported by a high school diploma or equivalent. Familiarity with annotation platforms, data management tools, and sometimes basic coding or spreadsheet software is typically required. Excellent time management, communication, and self-motivation help you consistently meet deadlines and quality standards while working independently. These skills and qualities ensure the precise labeling of data necessary for training reliable AI and machine learning models.

What are some common challenges faced by remote data annotators, and how can they be addressed?

Remote data annotators often encounter challenges such as maintaining focus during repetitive tasks, ensuring annotation accuracy, and communicating effectively with distributed teams. To overcome these, it's helpful to establish a structured work routine, take regular breaks to prevent fatigue, and leverage collaboration tools for clear communication with project managers and peers. Additionally, staying updated with project guidelines and seeking feedback can significantly improve both productivity and annotation quality.

What is the difference between Remote Data Annotator vs Remote Data Labeler?

AspectRemote Data AnnotatorRemote Data Labeler
CredentialsBasic computer skills, attention to detailBasic computer skills, attention to detail
Work EnvironmentRemote, flexible hoursRemote, flexible hours
Industry UsageAI, machine learning, data scienceAI, machine learning, data science
Job FocusAnnotating complex data types (images, videos)Labeling simpler data (images, text)

Remote Data Annotators typically handle complex data annotation tasks like videos and images, requiring more detailed work. Remote Data Labelers focus on simpler labeling tasks, often involving images or text. Both roles are remote, involve similar skills, and are used in AI and machine learning industries, but differ in complexity and scope of data handled.

More about Remote Data Annotator jobs
What cities are hiring for Remote Data Annotator jobs? Cities with the most Remote Data Annotator job openings:
What are the most commonly searched types of Data Annotator jobs? The most popular types of Data Annotator jobs are:
What states have the most Remote Data Annotator jobs? States with the most job openings for Remote Data Annotator jobs include:
What job categories do people searching Remote Data Annotator jobs look for? The top searched job categories for Remote Data Annotator jobs are:
Remote Data Annotator jobs near you
Infographic showing various Remote Data Annotator job openings in the United States as of May 2026, with employment types broken down into 95% Full Time, 3% Part Time, and 2% Contract. Highlights an 56% Physical, 1% Hybrid, and 43% Remote job distribution, with an average salary of $165,018 per year, or $79.3 per hour.

Data Annotator

Mercor

New York, NY • Remote

$50/hr

Full-time

Posted 24 days ago

Job description

About the job

Mercor connects elite creative and technical talent with leading AI research labs. Headquartered in San Francisco, our investors include Benchmark, General Catalyst, Peter Thiel, Adam D'Angelo, Larry Summers, and Jack Dorsey.

Position: Generalist
Type: Contract
Compensation: $50/hour
Location: Remote

Role Responsibilities

  • Review, evaluate, and annotate AI outputs with extreme attention to detail.
  • Follow complex guidelines precisely and apply them consistently across tasks.
  • Identify subtle errors, edge cases, and quality issues others might miss.
  • Provide clear, structured feedback to improve downstream AI training quality.
  • Maintain high accuracy across repetitive, high-volume workflows.
  • Flag unclear instructions or ambiguous cases proactively.

Qualifications

Must-Have

  • Exceptionally detail-oriented and quality-obsessed mindset.
  • Prior experience as a CB / reviewer / rater in human data or AI training pipelines.
  • Proven ability to follow nuanced instructions without deviation.
  • Strong written communication and reasoning skills.
  • High reliability, consistency, and comfort with repetitive precision work.
  • Ability to work independently and maintain focus over long task batches.

Preferred

  • Experience with large-scale AI data annotation or evaluation programs.
  • Background in QA, operations, trust & safety, or structured review work.
  • Familiarity with multi-step rubric-based evaluations.
  • Comfort giving calibrated feedback aligned with strict quality bars.

Compensation & Legal

  • Hourly contractor
  • Paid weekly via Stripe Connect

Application Process (Takes 20–30 mins to complete)

  • Upload resume
  • AI interview based on your resume
  • Submit form

Resources & Support

  • For details about the interview process and platform information, please check: https://talent.docs.mercor.com/welcome/welcome
  • For any help or support, reach out to: support@mercor.com

PS: Our team reviews applications daily. Please complete your AI interview and application steps to be considered for this opportunity.