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
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
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.