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Remote Data Annotator Jobs (NOW HIRING)

Toptal

Talent Network: Senior Project Leader

This is a remote position. We do not offer visa sponsorship or assistance. Resumes and ... data/AI, or similar) * Proven ability to manage complex workflows and distributed teams * Strong ...

Toptal

This is a remote position. We do not offer visa sponsorship or assistance. Resumes and ... data/AI, or similar) * Proven ability to manage complex workflows and distributed teams * Strong ...

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Remote Data Annotator information

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$46K

$165K

$243.5K

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.
Multimedia Generative AI Analyst - USA (Remote)

Multimedia Generative AI Analyst - USA (Remote)

Welo Data

Charleston, WV • Remote

$28.80/hr

Full-time

Posted 16 days ago

Job description

About the Role
We are hiring full-time Generative AI Analysts in the United States to support evaluation and quality review of AI-generated videos. In this role, you will review text prompts, watch corresponding video outputs, and identify mismatches, inconsistencies, and visual errors.
 
This role is best suited for candidates with strong attention to detail, excellent visual comprehension, and the ability to follow structured guidelines consistently. Candidates should be comfortable reviewing video content, comparing visual outputs against written prompts, and writing clear, concise annotations. A solid understanding of US driving and road rules is especially important, as some tasks may involve roadway scenarios, vehicle behavior, and basic robotics behavior in real-world environments. 
 
Project Details
  • Job Title: Generative AI Analyst
  • Location: Remote, USA
  • Hours: 40 hours per week
  • Employment Type: W2 Full-Time Employee
  • Pay Rate: $28.80/hour
What You’ll Do
  • Review text prompts and corresponding AI-generated video clips to identify mismatches, inconsistencies, and visual errors.
  • Tag specific parts of the prompt that do not match the video by identifying only the incorrect prompt text, rather than the full sentence unless needed.
  • Add visual or behavioral errors as annotation instances in annotation platform.
  • Write brief, clear descriptions for each error instance.
  • Avoid duplicate annotations by ensuring errors already captured as prompt mismatches are not added again as separate instances.
  • Evaluate video content for actions, context, motion, scene consistency, object behavior, and prompt alignment.
  • Apply project guidelines consistently across repetitive, detail-oriented tasks.
  • Use critical thinking and judgment to handle ambiguous scenarios and determine the most accurate ground truth.
  • Identify recurring or systematic errors across tasks and document examples for review.
  • Perform self-QA on completed work and correct errors before submission.
  • Participate in calibration sessions to align interpretation of guidelines and reduce annotator-to-annotator variance.
  • Incorporate feedback from quality reviews into subsequent work.
  • Support throughput and quality targets while maintaining accuracy at scale.
Requirements:
  • Experience in video annotation, multimedia annotation, content quality review, data labeling, computer vision labeling, Generative AI evaluation, or a closely related field.
  • Work Authorization is required for the role.
  • Strong attention to detail and ability to identify subtle errors, mismatches, and inconsistencies between prompts and videos.
  • Solid understanding of US driving rules, road behavior, traffic scenarios, and roadway conventions.
  • Good reading comprehension and ability to accurately compare written prompts against visual outputs.
  • Strong written communication skills in English, with the ability to describe errors clearly and concisely.
  • Ability to follow detailed guidelines consistently and maintain high accuracy across repetitive tasks.
  • Critical thinking and sound judgment when reviewing ambiguous or complex scenarios.
  • Basic understanding of robotics behavior in real-world environments.
  • Comfortable working in structured annotation platforms or similar tools.
  • Ability to maintain focus and quality while reviewing multimedia content for extended periods.
Ways to Stand Out from the Crowd
  • Prior experience evaluating AI-generated video, synthetic media, autonomous driving data, robotics scenarios, or traffic-related visual content.
  • Familiarity with US traffic rules, road signage, lane behavior, vehicle interactions, pedestrian behavior, and common driving scenarios.
  • Experience with QA, audit, or second-pass review workflows, including calibration, sampling, defect tracking, or error taxonomy development.
  • Ability to identify recurring model failure patterns across tasks or batches.
Please note that in order to verify work authorization as is required by Federal law (I-9 process), all new employees must complete a live video verification with their selected IDs and provide photos of these selected IDs within their first 3 days of employment.
 
To know more details (Click here)
 
In compliance with federal law, all persons hired will be required to verify identity and eligibility to work in the United States and to complete the required employment eligibility verification form upon hire.  In addition, we employ anti-fraud checks to ensure all candidates meet the requirements of the program.
 
 
As a trusted global transformation partner, Welocalize accelerates the global business journey by enabling brands and companies to reach, engage, and grow international audiences. Welocalize delivers multilingual content transformation services in translation, localization, and adaptation for over 250 languages with a growing network of over 400,000 in-country linguistic resources. Driving innovation in language services, Welocalize delivers high-quality training data transformation solutions for NLP-enabled machine learning by blending technology and human intelligence to collect, annotate, and evaluate all content types. Our team works across locations in North America, Europe, and Asia serving our global clients in the markets that matter to them. www.welocalize.com
 
To perform this job successfully, an individual must be able to perform each essential duty satisfactorily. The requirements listed below are representative of the knowledge, skill, and/or ability required. Reasonable accommodations may be made to enable individuals with disabilities to perform essential functions.

We may use artificial intelligence (AI) tools to support parts of the hiring process, such as reviewing applications, analyzing resumes, or assessing responses. These tools assist our recruitment team but do not replace human judgment. Final hiring decisions are ultimately made by humans. If you would like more information about how your data is processed, please contact us.

Working at Welo Data

What to expect from working at Welo Data

From Welo Data

About Welo Data, in their own words

From Welo Data

Welo Data is a global AI data services company powering the next generation of AI. We build, annotate, and validate the training datasets that make AI models accurate, safe, and ready for the real world — across languages, cultures, and domains.

Our team of experts spans the globe, combining deep technical knowledge with a human-centered approach. If you want your work to shape how AI understands the world, you'll find your place here.

Diversity and inclusion statement

From Welo Data

Our Strength is derived from Winning Together. Welo Data is unequivocally committed to developing and fostering a workplace and organizational culture that values the diversity of thought and perspective delivered by a diverse global workforce operating within an inclusive organization.