Linguistic quality and localisation QA: a translator’s route into AI work
· a.pannella87
Last updated: 27 October 2026 · OpenJob editorial team
Linguistic quality assessment marks errors by category, such as accuracy, fluency, terminology, style and locale conventions, and gives each a severity. AI language projects use the same framework to judge text written by models. Localisation QA adds context: how the text works on a screen or in an app. Translators already have most of these skills.
Key points
- Standard LQA categories: accuracy, fluency, terminology, style, locale.
- Every marked error gets a severity level.
- Teaching or CEFR assessment experience is requested in several listings.
- Write the correction and a one-line reason for every error.
A sentence can be grammatically correct and still sound translated. Spotting that gap, and explaining it, is the centre of linguistic quality work, whether the text was written by a person or a model.
What an LQA reviewer marks
Classic linguistic quality assessment uses error categories: accuracy (meaning changed), fluency (grammar, spelling), terminology, style and locale conventions such as dates or currency. Each error gets a severity. AI projects borrow this framework almost unchanged, because it turns a feeling (“this is off”) into data.
What localisation QA adds
Localisation testers look at text in context: on a screen, in a button, in an app flow. A translation that fits the dictionary may overflow the button or use the wrong form of address. When AI projects test localisation, they want the same eye for context.
Teaching background helps
Several current listings ask for experience teaching a language or assessing learners against CEFR levels, because the work involves judging learner-style text. Examples: AI Language Expert – Italian, AI Language Expert – French, AI Language Expert – Japanese.
A habit worth building
When you mark an error, write the correction and a one-line reason. “Unnatural: Italian would use the impersonal ‘si’ here” is useful to a reviewer; “sounds wrong” is not. Projects measure the usefulness of your feedback as much as its accuracy.
Native-speaker review roles in several languages are listed on OpenJob, including Linguist – Spanish (Puerto Rico) and German Language Expert.
Open roles you can apply to from anywhere
Refreshed automatically from our verified catalogue. Check eligible countries and requirements on each listing.
Corporate Attorney (BigLaw Firms)
Remote contract work for corporate attorneys from large law firms on an AI training project: analyze and draft complex agreements and legal instruments in corporate law, M&A, private equity and cap…
Equity Research Expert
Remote contract for equity research professionals: review and build datasets that model real equity research work, analyze earnings reports, revise estimates and synthesize peer benchmarking for AI…
Open Source GitHub Maintainer
micro1 is engaging expert Senior Software Engineers to support an innovative project.
Bilingual Japanese Psychologist (PhD)
Remote contract for bilingual psychologists: assess psychological case studies and documentation and develop culturally sensitive scenarios and materials in Japanese and English for AI training.
Physics Expert (PhD / Postdoc)
micro1 is engaging Physics Experts (PhD / Postdoc) to contribute deep scientific knowledge and problem-solving skills to a high-impact customer project.
Language and AI roles · Translation roles
Frequently asked questions
Can translators work in AI training?
Yes. Linguistic quality work for AI uses the same error categories translators know: accuracy, fluency, terminology and style. Projects look for native speakers who can explain why a sentence sounds translated. Teaching experience and familiarity with CEFR levels also help for some roles.
What is the difference between LQA and localisation QA?
LQA judges the text itself by error category and severity. Localisation QA checks the text in context, such as a button, a screen or an app flow, where a correct translation may still be too long or use the wrong form of address.
How should I write feedback on a language error?
Give the correction and a one-line reason. For example: unnatural, Italian would use the impersonal si here. Feedback like sounds wrong gives the reviewer nothing to act on. Projects measure the usefulness of your comments as well as their accuracy.