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Language Annotator Jobs (NOW HIRING)

... in annotator performance, task complexity, and data characteristics to help optimize task design ... Experience with the deployment of Large Language Models / Generative AI in service of efficiency in ...

Native fluency in the target language * Experience as AI reviewer, annotator, or evaluator preferred * Comfortable working with both textual and audio/video materials * Ability to follow detailed ...

Native fluency in the target language * Strong command of English * Experience as AI reviewer, annotator, or evaluator preferred * Comfortable working with both textual and audio/video materials

Native fluency in the target language * Strong command of English * Experience as AI reviewer, annotator, or evaluator preferred * Comfortable working with both textual and audio/video materials

Native fluency in the target language * Strong command of English * Experience as AI reviewer, annotator, or evaluator preferred * Comfortable working with both textual and audio/video materials

Native fluency in the target language * Strong command of English * Experience as AI reviewer, annotator, or evaluator preferred * Comfortable working with both textual and audio/video materials

Responsibilities : • Annotate data accurately and consistently according to predefined guidelines in the required language. • Perform basic research as needed to ensure accurate annotation. • ...

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Language Annotator information

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$32K

$44.1K

$51K

How much do language annotator jobs pay per year?

As of Jul 11, 2026, the average yearly pay for language annotator in the United States is $44,079.00, according to ZipRecruiter salary data. Most workers in this role earn between $39,500.00 and $50,000.00 per year, depending on experience, location, and employer.

What does a language annotator do?

A language annotator labels and tags text data to help improve natural language processing systems. They analyze language features such as syntax, semantics, and context, often using specialized tools and following detailed guidelines. This work supports the development of AI models, speech recognition, and machine translation applications.

What are Language Annotators?

Language Annotators are professionals who label, categorize, and tag text, audio, or speech data to help train and improve natural language processing systems and AI models. Their work involves identifying linguistic features such as parts of speech, named entities, sentiment, or intent in language data. Language Annotators play a crucial role in making AI technologies like chatbots, translation tools, and voice assistants more accurate and effective. They often work with large datasets and follow specific guidelines to ensure consistency and quality in the annotations.

What are the key skills and qualifications needed to thrive as a Language Annotator, and why are they important?

To thrive as a Language Annotator, you need strong linguistic knowledge, attention to detail, and typically a background in linguistics or a related field. Familiarity with annotation tools, text analysis software, and version control systems like Git is often required. Excellent communication, critical thinking, and the ability to follow detailed guidelines are essential soft skills. These skills ensure the production of high-quality, consistent data crucial for training effective language models and supporting NLP research.

Is linguistics in high demand?

Linguistics-related roles, including language annotators, are increasingly in demand due to growth in natural language processing, machine learning, and AI technologies. Skills in language analysis, annotation tools, and understanding of linguistic structures enhance employability in this field.

What are some common challenges faced by Language Annotators, and how can they be managed effectively?

Language Annotators often encounter challenges such as maintaining consistency in annotation, managing large volumes of data, and adapting to evolving guidelines. To address these, it's important to communicate regularly with team members, participate in calibration sessions, and seek clarification when guidelines are unclear. Utilizing annotation tools efficiently and staying organized can also help manage workload and ensure high-quality results.

How much do AI annotators make?

AI annotators typically earn between $12 and $20 per hour, depending on experience, location, and the complexity of the annotation tasks. Many positions are freelance or part-time, often requiring attention to detail and familiarity with annotation tools.

What qualifications do you need to be a data annotator?

To be a language annotator, candidates typically need strong language skills, attention to detail, and basic computer proficiency. Some roles may require familiarity with annotation tools or specific training, but formal certifications are not usually mandatory.
More about Language Annotator jobs
Infographic showing various Language Annotator job openings in the United States as of July 2026, with employment types broken down into 6% Internship, 74% As Needed, 1% Full Time, 1% Contract, 16% Nights, and 2% Summer. Highlights an 39% Physical, 1% Hybrid, and 60% Remote job distribution, with an average salary of $44,079 per year, or $21.2 per hour.
Data Scientist, AIML Data Scientist

Data Scientist, AIML Data Scientist

Apple

Cupertino, CA • On-site

Full-time

Re-posted 8 days ago


Apple rating

8.1

Company rating: 8.1 out of 10

Based on 670 frontline employees who took The Breakroom Quiz

5th of 30 rated technology retailers


Job description

Imagine what you could do here. At Apple, new ideas have a way of becoming extraordinary products, services, and customer experiences very quickly. Do you love thinking analytically? Are you passionate about solving complex business problems in a fast-paced environment? The AIML Data Operations group engages with teams across Apple's ecosystem with the ultimate goal of delivering high-quality annotated data in support of unreleased products and ground breaking AI technology. Within the Data Operations organization, the Capacity Planning & Analytics team provides forecasting, capacity planning and optimization, data products, metrics reporting, modeling & experimentation, and ad hoc analyses.
We are seeking a highly motivated Senior Data Scientist to lead analysis into annotation project trends to uncover patterns in annotator performance, task complexity, and data characteristics to help optimize task design. You will translate behavioral insights and empirical findings into optimized project structures and workflows, and power capacity planning & optimization with quantitative rigor-all to ensure we consistently launch projects that are smarter in design, faster in execution, and uncompromising in quality. You will partner closely with Data Ops Client Engagement, Human Factors engineering and annotation customers to collaborate on the most effective methods.
Description
The ideal candidate for this role is an experienced data scientist with deep expertise in analytics and experimentation, who excels at building strong cross-functional relationships to drive data-informed decisions across the company, and is skilled at partnering with operations and engineering teams to surface and communicate key data insights that improve performance and customer experience at a global scale.
Minimum Qualifications
Bachelors degree in Computer Science, Statistics, Mathematics, Engineering, Economics or related field.
4+ years of experience in data science with proven skills in developing meaningful and concise analytic objectives from general business goals
Tested capabilities and comfort in scalable schema designs, relational database and big data technologies, ETL, code management, and query performance optimization
Mastery in SQL-based languages, and proficiency in at least one large-scale data languages
Strong hands-on experience interpretable with machine learning models and sophisticated analytic solutions using scripting tools such as Python or R
Preferred Qualifications
Masters degree or PhD in Computer Science, Statistics, Mathematics, Engineering, Economics or related field.
Experience with the deployment of Large Language Models / Generative AI in service of efficiency in operations
Excellent communication and presentation skills with meticulous attention to detail and the ability to collaborate effectively between business and analytic teams at multiple levels of the organization
Passion for AIML and Operations, with a consistent track record of operational results.

What Apple employees say

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Benefits

Hours and flexibility

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About Apple

Sourced by ZipRecruiter

Imagine what you could do here! At Apple, new ideas have a way of becoming extraordinary products, services, and customer experiences very quickly. Bring passion and dedication to your job and there's no telling what you could accomplish. Dynamic, intelligent people and inspiring, innovative technologies are the norm here. The people who work here have reinvented entire industries with all Apple Hardware products. The same real passion for innovation that goes into our products also applies to our practices strengthening our dedication to leave the world better than we found it.

Industry

Computer and electronic product manufacturing

Company size

10,000+ Employees

Headquarters location

Cupertino, CA, US

Year founded

1976