Senior NLP Corpus Quality Architect (Remote)

Agile 4UX; Abu Dhabi; Remote; AED 350,000 - 550,000; Full time

Benefits offered by this job

100% remote work

Competitive compensation

Professional development

Collaboration with international teams

Job summary

Agile 4UX is seeking a Senior Natural Language Corpus Evaluation Specialist to lead the assessment and improvement of linguistic datasets used in AI, NLP, and ML projects. The role emphasizes accuracy, representativeness, and quality across multilingual corpora, with an emphasis on rigorous evaluation frameworks.

You will collaborate with NLP engineers and researchers, establish standards, review annotations, and develop repeatable QA procedures in a fully remote environment.

Qualifications

• Bachelor's or master's degree in Computational Linguistics, Linguistics, NLP, CS, Data Science, or related field.
• Significant experience in corpus evaluation, NLP dataset quality assurance, or linguistic data management.
• Advanced understanding of linguistic structures, language variation, and text analysis methodologies.

Responsibilities

• Lead evaluations of large-scale natural language corpora across monolingual and multilingual datasets.
• Establish corpus quality standards, evaluation frameworks, scoring criteria, and thresholds.
• Collaborate with NLP engineers and researchers to improve dataset quality.
• Develop sampling methodologies and statistical procedures to measure corpus quality.

Education

Bachelor's or master's degree in Computational Linguistics / NLP / CS / Data Science

Tools

Python

NLP libraries

Job description

Agile 4UX is seeking a Senior Natural Language Corpus Evaluation Specialist to lead the assessment and improvement of linguistic datasets used in AI, NLP, and ML projects. The role emphasizes accuracy, representativeness, and quality across multilingual corpora, with an emphasis on rigorous evaluation frameworks.

You will collaborate with NLP engineers and researchers, establish standards, review annotations, and develop repeatable QA procedures in a fully remote environment.