... annotation, LLM evaluation, scientific QA, academic review, or rubric-based review. Company : Our Core mission is to develop, deploy, or integrate artificial intelligence (AI) -- including machine ...
... annotation, LLM evaluation, scientific QA, academic review, or rubric-based review. Company : Our Core mission is to develop, deploy, or integrate artificial intelligence (AI) -- including machine ...
... data annotation, LLM evaluation, scientific QA, academic review, psychology/neuroscience content review, or rubric-based review. Company : Our Core mission is to develop, deploy, or integrate ...
... data annotation, LLM evaluation, scientific QA, academic review, psychology/neuroscience content review, or rubric-based review. Company : Our Core mission is to develop, deploy, or integrate ...
... data annotation, LLM evaluation, SQL QA, code review, or rubric-based technical review. Company : Our Core mission is to develop, deploy, or integrate artificial intelligence (AI) -- including ...
... data annotation, LLM evaluation, SQL QA, code review, or rubric-based technical review. Company : Our Core mission is to develop, deploy, or integrate artificial intelligence (AI) -- including ...
... annotation, LLM evaluation, spreadsheet QA, or rubric-based review. Company : Our Core mission is to develop, deploy, or integrate artificial intelligence (AI) -- including machine learning (ML ...
... annotation, LLM evaluation, spreadsheet QA, or rubric-based review. Company : Our Core mission is to develop, deploy, or integrate artificial intelligence (AI) -- including machine learning (ML ...
... annotation, large language models, prompt/response evaluation, financial content QA, or rubric-based LLM evaluation. • Professional certifications such as CFA, CPA, ACCA, FRM, CMA, CA, or ...
... annotation, large language models, prompt/response evaluation, financial content QA, or rubric-based LLM evaluation. • Professional certifications such as CFA, CPA, ACCA, FRM, CMA, CA, or ...
... annotation, LLM evaluation, scientific QA, academic review, or rubric-based review. Company : Our Core mission is to develop, deploy, or integrate artificial intelligence (AI) -- including machine ...
... annotation, LLM evaluation, scientific QA, academic review, or rubric-based review. Company : Our Core mission is to develop, deploy, or integrate artificial intelligence (AI) -- including machine ...
... annotation, LLM evaluation, spreadsheet QA, or rubric-based review. Company : Our Core mission is to develop, deploy, or integrate artificial intelligence (AI) -- including machine learning (ML ...
... annotation, LLM evaluation, spreadsheet QA, or rubric-based review. Company : Our Core mission is to develop, deploy, or integrate artificial intelligence (AI) -- including machine learning (ML ...
... data annotation, LLM evaluation, scientific QA, academic review, psychology/neuroscience content review, or rubric-based review. Company : Our Core mission is to develop, deploy, or integrate ...
... data annotation, LLM evaluation, scientific QA, academic review, psychology/neuroscience content review, or rubric-based review. Company : Our Core mission is to develop, deploy, or integrate ...
... data annotation, LLM evaluation, SQL QA, code review, or rubric-based technical review. Company : Our Core mission is to develop, deploy, or integrate artificial intelligence (AI) -- including ...
... data annotation, LLM evaluation, SQL QA, code review, or rubric-based technical review. Company : Our Core mission is to develop, deploy, or integrate artificial intelligence (AI) -- including ...
... data annotation, LLM evaluation, scientific QA, academic review, psychology/neuroscience content review, or rubric-based review. Company : Our Core mission is to develop, deploy, or integrate ...
... data annotation, LLM evaluation, scientific QA, academic review, psychology/neuroscience content review, or rubric-based review. Company : Our Core mission is to develop, deploy, or integrate ...
... annotation, LLM evaluation, academic QA, fact-checking, or rubric-based review. Company : Our Core mission is to develop, deploy, or integrate artificial intelligence (AI) -- including machine ...
... annotation, LLM evaluation, academic QA, fact-checking, or rubric-based review. Company : Our Core mission is to develop, deploy, or integrate artificial intelligence (AI) -- including machine ...
Previous experience in data annotation, QA, or testing * Interest in AI, machine learning, or emerging technologies What We Offer * Paid, flexible task-based work * Opportunity to work on innovative ...
Quick apply
Previous experience in data annotation, QA, or testing * Interest in AI, machine learning, or emerging technologies What We Offer * Paid, flexible task-based work * Opportunity to work on innovative ...
AI/ML Data Contributor
Miami, FL · Remote
Previous experience in data annotation, QA, or testing * Interest in AI, machine learning, or emerging technologies What We Offer * Paid, flexible task-based work * Opportunity to work on innovative ...
Quick apply
AI/ML Data Contributor
Miami, FL · Remote
Previous experience in data annotation, QA, or testing * Interest in AI, machine learning, or emerging technologies What We Offer * Paid, flexible task-based work * Opportunity to work on innovative ...
AI/ML Data Contributor
Louisville, KY · On-site
Previous experience in data annotation, QA, or testing * Interest in AI, machine learning, or emerging technologies What We Offer * Paid, flexible task-based work * Opportunity to work on innovative ...
AI/ML Data Contributor
Louisville, KY · On-site
Previous experience in data annotation, QA, or testing * Interest in AI, machine learning, or emerging technologies What We Offer * Paid, flexible task-based work * Opportunity to work on innovative ...
Previous experience in data annotation, QA, or testing * Interest in AI, machine learning, or emerging technologies What We Offer * Paid, flexible task-based work * Opportunity to work on innovative ...
Quick apply
Previous experience in data annotation, QA, or testing * Interest in AI, machine learning, or emerging technologies What We Offer * Paid, flexible task-based work * Opportunity to work on innovative ...
AI/ML Data Contributor
Chicago, IL · On-site
Previous experience in data annotation, QA, or testing * Interest in AI, machine learning, or emerging technologies What We Offer * Paid, flexible task-based work * Opportunity to work on innovative ...
AI/ML Data Contributor
Chicago, IL · On-site
Previous experience in data annotation, QA, or testing * Interest in AI, machine learning, or emerging technologies What We Offer * Paid, flexible task-based work * Opportunity to work on innovative ...
AI/ML Data Contributor
New York, NY · On-site
Previous experience in data annotation, QA, or testing * Interest in AI, machine learning, or emerging technologies What We Offer * Paid, flexible task-based work * Opportunity to work on innovative ...
AI/ML Data Contributor
New York, NY · On-site
Previous experience in data annotation, QA, or testing * Interest in AI, machine learning, or emerging technologies What We Offer * Paid, flexible task-based work * Opportunity to work on innovative ...
AI/ML Data Contributor
Des Moines, IA · Remote
Previous experience in data annotation, QA, or testing * Interest in AI, machine learning, or emerging technologies What We Offer * Paid, flexible task-based work * Opportunity to work on innovative ...
Quick apply
AI/ML Data Contributor
Des Moines, IA · Remote
Previous experience in data annotation, QA, or testing * Interest in AI, machine learning, or emerging technologies What We Offer * Paid, flexible task-based work * Opportunity to work on innovative ...
Strong understanding of AI/ML concepts, annotation workflows, and data quality assurance. * Basic knowledge of SQL and/or Python for data querying and scripting. * Ability to translate complex ...
Strong understanding of AI/ML concepts, annotation workflows, and data quality assurance. * Basic knowledge of SQL and/or Python for data querying and scripting. * Ability to translate complex ...
C++ QA Lead - Remote
$132K/yr
... annotation, LLM evaluation, code QA, or rubric-based code review. Company : Our Core mission is to develop, deploy, or integrate artificial intelligence (AI) -- including machine learning (ML), data ...
C++ QA Lead - Remote
$132K/yr
... annotation, LLM evaluation, code QA, or rubric-based code review. Company : Our Core mission is to develop, deploy, or integrate artificial intelligence (AI) -- including machine learning (ML), data ...
Annotation Qa information
See salary details
$24.52 - $29.06
9% of jobs
$29.06 - $33.61
7% of jobs
$33.61 - $38.16
7% of jobs
$38.35 is the 25th percentile. Wages below this are outliers.
$38.16 - $42.70
24% of jobs
The median wage is $43.03 / hr.
$42.70 - $47.25
29% of jobs
$47.25 - $51.79
14% of jobs
$51.79 - $56.34
7% of jobs
$56.34 - $60.88
2% of jobs
$60.88 - $65.43
0% of jobs
$65.43 - $69.97
0% of jobs
$69.97 - $74.52
0% of jobs
$24
$43
$74
How much do annotation qa jobs pay per hour?
As of Jul 14, 2026, the average hourly pay for annotation qa in the United States is $43.83, according to ZipRecruiter salary data. Most workers in this role earn between $38.70 and $47.84 per hour, depending on experience, location, and employer.
What is the difference between Annotation Qa vs Data Labeler?
| Aspect | Annotation Qa | Data Labeler |
|---|---|---|
| Required Credentials | Basic technical skills, sometimes certifications in data annotation tools | Basic computer skills, sometimes certifications in labeling software |
| Work Environment | Office or remote, collaborative with annotation teams | Remote or on-site, focused on labeling tasks |
| Industry Usage | Used in AI, machine learning, and data annotation companies | Common in AI, machine learning, and data preparation sectors |
| Search & Comparison Intent | Often compared for quality assurance roles in data annotation | Compared for entry-level data preparation roles |
Annotation Qa and Data Labeler roles are closely related in the data annotation industry. Annotation Qa focuses on quality assurance, reviewing and verifying labeled data, while Data Labelers perform the initial labeling tasks. Both require similar technical skills and work environments, but Annotation Qa emphasizes quality control processes. Understanding these differences helps employers and job seekers identify the right role based on skills and career goals.
How hard is it to get hired by data annotation?
Getting hired as a data annotation specialist generally requires basic computer skills, attention to detail, and familiarity with annotation tools. Many positions are entry-level and do not require advanced education, making the hiring process relatively accessible, though competition can vary based on the employer and job volume.
Is AI annotation legit?
AI annotation is a legitimate task involving labeling data to train machine learning models, often performed by annotation QA specialists to ensure accuracy. It requires attention to detail and familiarity with annotation tools, and is a common part of AI development workflows.
Is data annotation still hiring?
Data annotation roles are currently in demand as companies continue to develop AI and machine learning models. These jobs often require attention to detail and familiarity with annotation tools, and many positions are available for remote work with flexible schedules.
What is annotation qa?
Annotation QA (Quality Assurance) involves reviewing and verifying data annotations to ensure accuracy and consistency in datasets used for machine learning models. It typically requires attention to detail, understanding of annotation guidelines, and familiarity with annotation tools. The role helps improve data quality for training AI systems.
More about Annotation Qa jobs
What cities are hiring for Annotation Qa jobs? Cities with the most Annotation Qa job openings:
What states have the most Annotation Qa jobs? States with the most job openings for Annotation Qa jobs include:
What job categories do people searching Annotation Qa jobs look for? The top searched job categories for Annotation Qa jobs are:
Full-time
Posted 20 days ago
Job description
Job Summary:
YO IT Consulting is a fast-growing AI Data Services company delivering training data for many of the world’s largest AI companies and foundation-model labs. They are seeking a Geology Quality Assurance Lead to oversee quality and consistency across geology and earth science AI training projects, ensuring that all contributors follow expected quality standards and that the output is scientifically accurate and well-documented.
Responsibilities:
• Quality monitoring: Spot-check geology/earth science items, identify quality issues, provide ongoing feedback through DMs, and escalate recurring or critical issues.
• Scientific review: Evaluate AI-generated geology explanations, earth science summaries, geologic process descriptions, map/data interpretations, climate or hazard explanations, and step-by-step reasoning for accuracy and clarity.
• Trainer and QA communication: Update trainers and QAs on Discord about new item guidelines, project changes, workflow updates, quality expectations, and geology/earth-science-specific review standards.
• Question handling: Respond to trainer/QA questions clearly and promptly, especially around geologic timescales, rock/mineral identification, earth systems, natural hazards, spatial reasoning, environmental interpretation, and rubric interpretation.
• Trainer/QA activation management: DM contributors who are inactive or not working, encourage activation, track follow-ups, and flag availability issues when needed.
• Documentation: Create and maintain geology/earth science project documentation, including style guides, trackers, FAQs, quality notes, examples, honeypots, calibration tasks, and onboarding materials.
• Onboarding and training: Schedule and run onboarding/training calls with trainers and QAs to explain project expectations, workflows, rubrics, quality standards, and geology/earth-science-specific review requirements.
• Quality alignment: Ensure all trainers and QAs apply geology/earth science review guidelines consistently and understand updates as projects evolve.
• Risk review: Flag misleading, overconfident, geologically impossible, environmentally unsupported, or poorly contextualized earth science claims.
• Process improvement: Identify recurring quality gaps, propose workflow improvements, and help build scalable QA processes for earth science/geology AI training projects.
Qualifications:
Required:
• Bachelor’s, Master’s, or PhD degree in Geology, Earth Sciences, Geoscience, Environmental Science, Geophysics, Geochemistry, Hydrology, Paleontology, Oceanography, or a closely related field.
• Strong grasp of the English language to follow project guidelines, communicate with teams, and provide clear written feedback.
• 3+ years of experience in geology/earth science research, teaching, fieldwork, environmental consulting, geospatial analysis, academic review, science communication, or related workflows.
• Strong understanding of plate tectonics, rock cycle, mineralogy, stratigraphy, geologic time, structural geology, geomorphology, natural hazards, climate systems, hydrology, and earth system processes.
• Ability to evaluate earth science/geology content against detailed rubrics and identify issues such as incorrect geologic processes, wrong timescales, misleading causal claims, flawed map/data interpretation, unsupported environmental claims, or oversimplified explanations.
• Comfortable working in fast-moving remote environments using tools such as Discord, Google Sheets, Google Docs, trackers, dashboards, and project management systems.
• Highly detail-oriented and organized, with the ability to maintain style guides, FAQs, trackers, onboarding materials, calibration tasks, and documentation.
Preferred:
• Familiarity with tools or methods such as GIS, remote sensing, geologic mapping, field methods, core/log interpretation, geochemical data, climate datasets, Python/R, or scientific visualization.
• Experience leading or supporting remote teams of researchers, educators, reviewers, environmental specialists, annotators, or QAs.
• Experience with AI training, data annotation, LLM evaluation, scientific QA, academic review, or rubric-based review.
Company:
Our Core mission is to develop, deploy, or integrate artificial intelligence (AI) — including machine learning (ML), data analytics, automation, natural language processing (NLP), computer vision, and related technologies — to solve real-world problems, improve decision-making, automate repetitive tasks, and deliver intelligent solutions across industries. Founded in 2018, the company is headquartered in Abu Dhabi, Abu Dhabi Emirate, AE, , with a team of 51-200 employees. The company is currently Growth Stage.
YO IT Consulting is a fast-growing AI Data Services company delivering training data for many of the world’s largest AI companies and foundation-model labs. They are seeking a Geology Quality Assurance Lead to oversee quality and consistency across geology and earth science AI training projects, ensuring that all contributors follow expected quality standards and that the output is scientifically accurate and well-documented.
Responsibilities:
• Quality monitoring: Spot-check geology/earth science items, identify quality issues, provide ongoing feedback through DMs, and escalate recurring or critical issues.
• Scientific review: Evaluate AI-generated geology explanations, earth science summaries, geologic process descriptions, map/data interpretations, climate or hazard explanations, and step-by-step reasoning for accuracy and clarity.
• Trainer and QA communication: Update trainers and QAs on Discord about new item guidelines, project changes, workflow updates, quality expectations, and geology/earth-science-specific review standards.
• Question handling: Respond to trainer/QA questions clearly and promptly, especially around geologic timescales, rock/mineral identification, earth systems, natural hazards, spatial reasoning, environmental interpretation, and rubric interpretation.
• Trainer/QA activation management: DM contributors who are inactive or not working, encourage activation, track follow-ups, and flag availability issues when needed.
• Documentation: Create and maintain geology/earth science project documentation, including style guides, trackers, FAQs, quality notes, examples, honeypots, calibration tasks, and onboarding materials.
• Onboarding and training: Schedule and run onboarding/training calls with trainers and QAs to explain project expectations, workflows, rubrics, quality standards, and geology/earth-science-specific review requirements.
• Quality alignment: Ensure all trainers and QAs apply geology/earth science review guidelines consistently and understand updates as projects evolve.
• Risk review: Flag misleading, overconfident, geologically impossible, environmentally unsupported, or poorly contextualized earth science claims.
• Process improvement: Identify recurring quality gaps, propose workflow improvements, and help build scalable QA processes for earth science/geology AI training projects.
Qualifications:
Required:
• Bachelor’s, Master’s, or PhD degree in Geology, Earth Sciences, Geoscience, Environmental Science, Geophysics, Geochemistry, Hydrology, Paleontology, Oceanography, or a closely related field.
• Strong grasp of the English language to follow project guidelines, communicate with teams, and provide clear written feedback.
• 3+ years of experience in geology/earth science research, teaching, fieldwork, environmental consulting, geospatial analysis, academic review, science communication, or related workflows.
• Strong understanding of plate tectonics, rock cycle, mineralogy, stratigraphy, geologic time, structural geology, geomorphology, natural hazards, climate systems, hydrology, and earth system processes.
• Ability to evaluate earth science/geology content against detailed rubrics and identify issues such as incorrect geologic processes, wrong timescales, misleading causal claims, flawed map/data interpretation, unsupported environmental claims, or oversimplified explanations.
• Comfortable working in fast-moving remote environments using tools such as Discord, Google Sheets, Google Docs, trackers, dashboards, and project management systems.
• Highly detail-oriented and organized, with the ability to maintain style guides, FAQs, trackers, onboarding materials, calibration tasks, and documentation.
Preferred:
• Familiarity with tools or methods such as GIS, remote sensing, geologic mapping, field methods, core/log interpretation, geochemical data, climate datasets, Python/R, or scientific visualization.
• Experience leading or supporting remote teams of researchers, educators, reviewers, environmental specialists, annotators, or QAs.
• Experience with AI training, data annotation, LLM evaluation, scientific QA, academic review, or rubric-based review.
Company:
Our Core mission is to develop, deploy, or integrate artificial intelligence (AI) — including machine learning (ML), data analytics, automation, natural language processing (NLP), computer vision, and related technologies — to solve real-world problems, improve decision-making, automate repetitive tasks, and deliver intelligent solutions across industries. Founded in 2018, the company is headquartered in Abu Dhabi, Abu Dhabi Emirate, AE, , with a team of 51-200 employees. The company is currently Growth Stage.