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Full Time Ai Language Trainer Jobs (NOW HIRING)

Oxy

Senior AI Language Model Engineer

Houston, TX · On-site

$99K - $137K/yr

... of AI Language Model Engineer within our AI Center of Excellence group based in Houston, TX. ... We will never: • Ask you to pay for applications, interviews, meetings, processing, training or ...

Oxy

Senior AI Language Model Engineer

Houston, TX · On-site

$99K - $137K/yr

... of AI Language Model Engineer within our AI Center of Excellence group based in Houston, TX. ... Ask you to pay for applications, interviews, meetings, processing, training or for any other fees ...

Weekday AI

Artificial Intelligence Manager

New York, NY · On-site

New York JobType: full-time AI Delivery Manager NYC, NY - Onsite Only Full-Time (FTE) Position ... Large Language Model (LLM) applications (RAG, Agents, Copilots) * Data science and machine learning ...

Weekday AI

Artificial Intelligence Manager

New York, NY · On-site

New York JobType: full-time AI Delivery Manager NYC, NY - Onsite Only Full-Time (FTE) Position ... Large Language Model (LLM) applications (RAG, Agents, Copilots) * Data science and machine learning ...

Kaspar Companies

AI Specialist

Shiner, TX · On-site

Kaspar Companies is seeking a full-time AI Specialist to lead their AI-driven initiatives. This role is responsible for training AI models, implementing AI solutions, and enhancing manufacturing ...

Fluency

AI Engineer

San Francisco, CA · On-site

They are seeking a full-time AI Engineer to develop and improve user-facing AI features by creating ... post-training or fine-tuning • Experience deploying AI features on AWS Lambda, ECS Fargate, or ...

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Full Time Ai Language Trainer information

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How much do full time ai language trainer jobs pay per hour?

As of Aug 28, 2026, the average hourly pay for full time ai language trainer in the United States is $31.24, according to ZipRecruiter salary data. Most workers in this role earn between $19.95 and $35.58 per hour, depending on experience, location, and employer.

What does a full time AI language trainer do?

A Full Time AI Language Trainer is responsible for teaching, training, and refining artificial intelligence language models. This involves curating and annotating data, evaluating model outputs, and providing feedback to improve the AI’s understanding of language. Language trainers collaborate with data scientists and engineers to develop algorithms and processes that enhance natural language processing capabilities. Their work helps ensure AI systems generate more accurate, contextually relevant, and ethical language responses.

What are the key skills and qualifications needed to thrive as a full time AI language trainer, and why are they important?

To thrive as a Full Time AI Language Trainer, you need strong linguistic expertise, analytical thinking, and a background in language or computational linguistics, often supported by a relevant degree. Familiarity with annotation tools, data labeling platforms, and machine learning systems is typically required, along with experience using productivity software. Excellent attention to detail, effective communication, and adaptability are valuable soft skills for collaborating with engineering teams and refining AI outputs. These skills and qualities ensure the creation of accurate, high-quality language data sets that directly impact the performance and reliability of AI language models.

What are some common challenges faced by full time AI language trainers, and how can they be addressed?

Full Time AI Language Trainers often encounter challenges such as maintaining data quality, staying updated with evolving language models, and managing large volumes of diverse training data. To address these, trainers typically collaborate closely with data scientists and engineers, utilize annotation tools to streamline workflows, and participate in regular team meetings to share best practices. Continuous learning and adapting to new technologies are also essential to ensure the AI models remain accurate and effective.

What is the difference between Full Time Ai Language Trainer vs Part Time Ai Language Tutor?

AspectFull Time Ai Language TrainerPart Time Ai Language Tutor
CredentialsTypically requires a degree in linguistics, education, or related field; certifications in language teaching or AI toolsMay have similar credentials but often less formal or fewer certifications
Work EnvironmentFull-time employment, often in corporate training centers or online platformsPart-time, often freelance or on-demand online sessions
Employer & Industry UsageUsed by educational institutions, tech companies, and online training platformsCommonly used by individual tutors, online marketplaces, and freelance platforms

In summary, a Full Time Ai Language Trainer typically works full-time in structured environments with formal credentials, while a Part Time Ai Language Tutor operates on a flexible schedule, often independently, with similar but sometimes fewer qualifications.

More about Full Time Ai Language Trainer jobs

What are the most commonly searched types of Ai Language Trainer jobs?

The most popular types of Ai Language Trainer jobs are:

What job categories do people searching Full Time Ai Language Trainer jobs look for?

The top searched job categories for Full Time Ai Language Trainer jobs are:

Full Time Ai Language Trainer jobs near you
Infographic showing various Full Time Ai Language Trainer job openings in the United States as of August 2026, with employment types broken down into 76% Full Time, 21% Part Time, and 3% Contract. Highlights an 64% Physical, 4% Hybrid, and 32% Remote job distribution, with an average salary of $64,984 per year, or $31.2 per hour.

Quality control specialist for AI/ ML with Polish language

Remote

TSMG
See more jobs at TSMGexternal

Full-time

Posted 8 days ago

Job description

About the Project

TSMG is looking for Quality control specialists to support an AI language project focused on improving speech recognition systems.

As a QC contributor, you will review completed language annotation tasks and ensure that AI-generated transcripts have been accurately converted into natural, readable display text according to the project guidelines. You will focus on identifying and correcting formatting, punctuation, capitalization, and text normalization issues.

What You Will Do
  • Review completed Display Transcription tasks for accuracy and consistency.
  • Compare the Display Transcription against the original lexical transcript and project guidelines.
  • Verify the correct use of:
    • punctuation;
    • capitalization;
    • numbers, dates, times, and currencies;
    • abbreviations and other text normalization rules.
  • Ensure that the original words and meaning have been preserved.
  • Identify and correct formatting or guideline-related errors.
  • Use the reference audio when necessary to verify ambiguous cases.
  • Apply project-specific quality standards consistently.
  • Provide accurate feedback and flag recurring issues when required.
  • Complete assigned QC tasks within project deadlines and productivity targets.
Requirements
  • Excellent written skills in the target language.
  • Strong attention to detail and accuracy.
  • Good understanding of punctuation, capitalization, and written language conventions.
  • Ability to identify inconsistencies and errors in formatted text.
  • Ability to follow detailed guidelines and apply them consistently.
  • Basic computer skills and a reliable internet connection.
  • Ability to work independently and meet quality and productivity targets.
  • Previous experience in transcription, proofreading, quality control, annotation, or linguistic projects is a plus.
  • Training and project guidelines will be provided before the project starts.
What We Offer
  • Opportunity to contribute to the development of AI and speech recognition technologies.
  • Flexible project-based work.
  • Clear guidelines and training before starting.
  • The opportunity to gain experience in AI language data and quality control projects.
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.
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