2

Remote Linguistic Tester Jobs (NOW HIRING)

... Linguistics, Law, Security Studies, Risk Analysis, or a related field. • Strong grasp of the ... adversarial testing, model evaluation, content moderation, or related workflows. • Strong ...

Conduct Localization QA (LQA) testing of live platform content, including music and app ... Review linguistic assessments, develop training materials and documentation for new projects, and ...

... Linguistics, Law, Security Studies, Risk Analysis, or a related field. • Strong grasp of the ... adversarial testing, model evaluation, content moderation, or related workflows. • Strong ...

AI Red Teamer

Washington, DC · On-site +1

$70K - $90K/yr

Requirements * Bachelor's degree-or equivalent experience-in CS, data science, linguistics ... Fully remote (U.S.-based) with flexible hours. * Comprehensive health, dental, and vision.

Remote Commitment: 10-20 hours/week Role Responsibilities * Transcribe and optimize audio and video ... Conduct model testing and grading, evaluating outputs for accuracy and clarity. * Provide ...

Remote Commitment: 10-20 hours/week Role Responsibilities * Transcribe and optimize audio and video ... Conduct model testing and grading to assess outputs for accuracy and fluency. * Provide structured ...

next page

Showing results 1-20

Remote Linguistic Tester information

See salary details

$11

$47

$69

How much do remote linguistic tester jobs pay per hour?

As of Jul 17, 2026, the average hourly pay for remote linguistic tester in the United States is $47.54, according to ZipRecruiter salary data. Most workers in this role earn between $37.50 and $56.01 per hour, depending on experience, location, and employer.

What is the difference between Remote Linguistic Tester vs Remote Language Analyst?

AspectRemote Linguistic TesterRemote Language Analyst
Required CredentialsLanguage proficiency, basic linguistic knowledgeAdvanced linguistic skills, possibly certifications
Work EnvironmentRemote, flexible hours, project-basedRemote, often more analytical tasks
Employer & Industry UsageTech companies, localization firms, testing servicesLocalization companies, research firms, tech industry
Common Search & ComparisonYesYes

Remote Linguistic Testers focus on evaluating language quality and testing linguistic accuracy, often on a project basis. Remote Language Analysts perform more in-depth analysis of language data, including linguistic research and interpretation. While both roles require language skills and remote work setups, Linguistic Testers typically handle testing tasks, whereas Language Analysts engage in detailed linguistic analysis.

More about Remote Linguistic Tester jobs
What cities are hiring for Remote Linguistic Tester jobs? Cities with the most Remote Linguistic Tester job openings:
What are the most commonly searched types of Linguistic Tester jobs? The most popular types of Linguistic Tester jobs are:
What states have the most Remote Linguistic Tester jobs? States with the most job openings for Remote Linguistic Tester jobs include:
Infographic showing various Remote Linguistic Tester job openings in the United States as of July 2026, with employment types broken down into 5% Locum Tenens, 3% As Needed, 65% Full Time, 19% Part Time, 2% Temporary, and 6% Nights. Highlights an 87% Physical, 1% Hybrid, and 12% Remote job distribution, with an average salary of $98,889 per year, or $47.5 per hour.

Full-time

Posted 28 days ago


Job description

Job Summary:
YO IT Consulting is a fast-growing AI Data Services company that delivers training data for major AI companies and foundation-model labs. They are seeking a Red-Teaming Quality Assurance Lead to oversee quality and consistency in AI red-teaming projects, ensuring that safety training data is realistic and policy-aligned. The role involves evaluating outputs, providing feedback, managing quality workflows, and supporting onboarding for contributors.
Responsibilities:
• Quality monitoring: Spot-check red-teaming items, identify quality issues, provide ongoing feedback through DMs, and escalate recurring or critical issues.
• Safety and red-team review: Evaluate adversarial prompts, model responses, risk classifications, safety analyses, policy explanations, and vulnerability reports for accuracy, realism, and usefulness.
• Trainer and QA communication: Update trainers and QAs on Discord about new item guidelines, project changes, workflow updates, quality expectations, and red-teaming-specific review standards.
• Question handling: Respond to trainer/QA questions clearly and promptly, especially around risk categories, adversarial strategy, policy boundaries, edge cases, severity, 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 red-teaming 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 red-teaming-specific review requirements.
• Quality alignment: Ensure all trainers and QAs apply red-teaming and safety-review guidelines consistently and understand updates as projects evolve.
• Risk review: Flag unsafe, low-quality, unrealistic, policy-inconsistent, or insufficiently documented red-team items.
• Process improvement: Identify recurring quality gaps, propose workflow improvements, and help build scalable QA processes for AI red-teaming projects.
Qualifications:
Required:
• Bachelor’s, Master’s, or professional experience in Computer Science, Cybersecurity, AI Safety, Trust & Safety, Public Policy, Psychology, Linguistics, Law, Security Studies, Risk Analysis, or a 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 AI safety, red-teaming, cybersecurity, trust and safety, content policy, risk analysis, adversarial testing, model evaluation, content moderation, or related workflows.
• Strong understanding of AI risk categories, adversarial prompting, jailbreak patterns, harmful-content taxonomies, misuse scenarios, policy interpretation, model behavior, and safety evaluation principles.
• Ability to evaluate red-teaming content against detailed rubrics and identify issues such as weak adversarial design, unrealistic scenarios, poor risk categorization, policy misinterpretation, unsafe outputs, or superficial vulnerability testing.
• Highly detail-oriented and organized, with the ability to maintain style guides, FAQs, trackers, onboarding materials, calibration tasks, and documentation.
Preferred:
• Familiarity with areas such as prompt injection, social engineering, cybersecurity abuse, fraud, self-harm safety, extremist content, misinformation, privacy risk, illicit behavior, bias, and model refusal behavior.
• Experience leading or supporting remote teams of red-teamers, reviewers, policy analysts, annotators, researchers, or QAs.
• Comfortable working in fast-moving remote environments using tools such as Discord, Google Sheets, Google Docs, trackers, dashboards, and project management systems.
• Experience with AI training, LLM evaluation, safety evaluations, content moderation QA, policy QA, 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.