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Research Linguist
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Research Linguist – Multilingual AI/NLP – HIRING ASAP
Location: Remote Working
Start Date: ASAP
Duration: 3-Month Contract (with extension)
Daily Rate: £240 - £350 per day PAYE (Negotiable)
Summary
We are looking for a Research Linguist to join a highly innovative multilingual AI research environment, working at the intersection of linguistics, NLP and Responsible AI.
This is an excellent opportunity for a PhD-qualified linguist to apply deep linguistic expertise to real-world AI systems, analysing model outputs across languages and helping improve the quality, safety and cultural understanding of multilingual AI.
Responsibilities
- You'll work closely with research scientists, machine learning/NLP engineers and native-language specialists to:
- Analyse large multilingual datasets and AI-generated language
- Conduct detailed linguistic error analysis of AI/LLM outputs and identify recurring or high-impact error patterns
- Research linguistic differences and similarities across a wide range of languages
- Develop and refine annotation guidelines for multilingual AI and translation projects
- Analyse areas of Responsible AI, including toxic language, hate speech, gender bias and cultural bias
- Conduct linguistic and NLP-focused literature reviews and summarise findings
- Evaluate the quality of linguistic data delivered by external vendors and provide actionable feedback
- Provide specialist guidance across typology, syntax, morphology, sociolinguistics, corpus linguistics, pragmatics, writing systems and phonology
- Collaborate with native speakers across different languages
- Use Python and SQL to analyse linguistic datasets
- Communicate research findings clearly to technical and research teams
- Contribute to research that may ultimately support academic publications
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Top 4 Skills Needed
- Solid grasp of General Linguistics theory at the research level: A strong academic foundation in general linguistics (with a PhD preferred) is essential, as candidates must be able to approach 100 to 1,600 languages from a theoretical standpoint rather than relying on knowing every specific language.
- Cross-functional communication and project management: The ability to work independently through ambiguous requests, prioritize and plan work, and communicate findings effectively with engineers and research scientists.
- Experience with Python: Proficiency to read, tweak, and execute data science notebooks (using tools like pandas) and query databases, as required for analyzing datasets and working alongside data scientists.
- A PhD in Linguistics or a closely related field: The degree must be fully finished (not in progress).
Key Skills
- A completed PhD in Linguistics or a closely related linguistic discipline
- 2-3 years of experience
- Native or near-native proficiency in a Bantu or Dravidian language
- Native or near-native proficiency in English
- Strong Python skills for data analysis
- Ability to query datasets using SQL
- Strong knowledge of:
- Language typology
- Syntax and morphology
- Sociolinguistics, including dialectology and discourse analysis
- Corpus linguistics
- Pragmatics
- Phonology
- Writing systems
- Some practical experience applying NLP techniques
- Excellent written communication and ability to communicate research findings to both technical and non-technical audiences
- Ability to independently manage complex research and analysis
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Skills Not Needed
- Computational Linguists: Candidates with a computer science background who have only taken an introductory linguistics course (e.g., a standard 16-week intro course found in some university programs) lack the necessary depth in theoretical linguistics.
- English Literature Graduates: An English literature degree is not a valid substitution for a linguistics degree.
- Candidates with In-Progress PhDs: Individuals currently completing or defending their PhD cannot manage the heavy workload alongside the demands of the role
- Non-Theoretical or Purely Applied Backgrounds: Anyone who lacks a strong theoretical foundation in general linguistics will struggle, as the role requires analysing languages far beyond standard or known sets.
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