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Vision Labeling Jobs (NOW HIRING)

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Senior Manager, Food Labeling

Beaverton, OR · On-site

Full-time employee benefits include medical, dental, vision, AD&D, life, 401(k) with discretionary ... The Senior Manager, Food Labeling is responsible for establishing, leading, and scaling Reser ...

BrightAI Corporation

Computer Vision Engineer

Palo Alto, CA

$131K - $154K/yr

Computer Vision Engineer - Data Labeling & Annotation Type: Temporary Duration: 6 months - 12 months What You'll Gain * Exposure to the full CV pipeline, from raw data to deployed model * Mentorship ...

Welocalize

Data Labeling Associate

Washington, DC

$34/hr

WHAT YOU'LL DO • Execute Data labelling and annotation tasks across speech and voice datasets ... Vision Insurance • Free Breakfast, Lunch, and Dinner (where applicable) • Stocked Micro ...

Welocalize

Data Labeling Associate

Burlingame, CA

$34/hr

WHAT YOU'LL DO • Execute Data labelling and annotation tasks across speech and voice datasets ... Vision Insurance • Free Breakfast, Lunch, and Dinner (where applicable) • Stocked Micro ...

Welocalize

Data Labeling Associate

Bellevue, WA

$34/hr

WHAT YOU'LL DO • Execute Data labelling and annotation tasks across speech and voice datasets ... Vision Insurance • Free Breakfast, Lunch, and Dinner (where applicable) • Stocked Micro ...

Welocalize

Data Labeling Associate

Washington, DC

$34/hr

WHAT YOU'LL DO • Execute Data labelling and annotation tasks across speech and voice datasets ... Vision Insurance • Free Breakfast, Lunch, and Dinner (where applicable) • Stocked Micro ...

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Vision Labeling information

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How much do vision labeling jobs pay per hour?

As of Jun 23, 2026, the average hourly pay for vision labeling in the United States is $13.97, according to ZipRecruiter salary data. Most workers in this role earn between $12.50 and $15.38 per hour, depending on experience, location, and employer.

What is vision labeling?

Vision labeling is the process of manually or automatically tagging objects, features, or attributes within images or videos. This data is essential for training computer vision models, which are used in applications like facial recognition, autonomous vehicles, and medical imaging. Vision labeling tasks can include identifying objects, outlining shapes, or classifying scenes. Accurate labeling helps improve the performance and reliability of artificial intelligence systems that rely on visual data.

What is the difference between Vision Labeling vs Data Annotation?

AspectVision LabelingData Annotation
CredentialsTypically requires basic technical skills, familiarity with labeling toolsSimilar, often requires understanding of annotation standards
Work EnvironmentData labeling platforms, remote or on-siteSame as Vision Labeling, often overlapping tools
Industry UsageUsed in AI training for computer vision tasksUsed across AI fields, including NLP and vision
Search & ComparisonFocused on visual data, images, videosBroader, includes text, audio, and visual data

Vision Labeling and Data Annotation are closely related roles in AI data preparation. Vision Labeling specifically involves tagging and categorizing visual data like images and videos, while Data Annotation encompasses a wider range of data types, including text and audio. Both roles require similar skills and tools, but Vision Labeling is specialized for computer vision projects.

What are the main challenges faced by vision labeling specialists, and how can they overcome them?

Vision labeling specialists often encounter challenges such as maintaining high accuracy when annotating complex images, managing repetitive tasks, and meeting tight project deadlines. To overcome these issues, it helps to stay updated on best practices, use quality control tools provided by the employer, and actively participate in team discussions to clarify ambiguous cases. Collaborating closely with machine learning engineers and team leads also ensures labels meet project requirements and helps address any uncertainties quickly.

What are the key skills and qualifications needed to thrive as a Vision Labeling Specialist, and why are they important?

To thrive as a Vision Labeling Specialist, you need strong attention to detail, basic computer literacy, and familiarity with image annotation concepts, often supported by a high school diploma or relevant experience. Proficiency with labeling platforms such as Labelbox, Supervisely, or CVAT, as well as understanding data annotation guidelines, is typically required. Patience, consistency, and effective communication help individuals excel in repetitive tasks and collaborate with quality assurance teams. These skills and qualities are vital to ensure the accuracy and reliability of labeled datasets used to train computer vision models.
More about Vision Labeling jobs
What cities are hiring for Vision Labeling jobs? Cities with the most Vision Labeling job openings:
What states have the most Vision Labeling jobs? States with the most job openings for Vision Labeling jobs include:
What job categories do people searching Vision Labeling jobs look for? The top searched job categories for Vision Labeling jobs are:
Vision Labeling jobs near you
Infographic showing various Vision Labeling job openings in the United States as of June 2026, with employment types broken down into 6% Full Time, and 94% Part Time. Highlights an 97% Physical, 1% Hybrid, and 2% Remote job distribution, with an average salary of $29,053 per year, or $14 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 2 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 and identifying potential inconsistencies or verification signals in application materials based on available information. 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.