Linguist

Responsibilities: Perform linguistic analyses on large datasets. Perform linguistic error analysis of AI model outputs, determining what the most frequent and severe error categories are. Write and revise guidelines for human annotation and other AI projects, including but not limited to translation tasks. Conduct typological and sociolinguistic research on a large number of languages, highlighting their similarities and differences. Perform linguistic analyses for Responsible AI (toxic language, hate speech, gender bias and other cultural biases) in massively multilingual settings. Conduct linguistic literature reviews on various NLP-adjacent topics, and summarize findings. Compare the quality of deliveries between vendors, identify error patterns, and provide actionable feedback. Provide information or guidance relative to any aspect of linguistic knowledge (typology, morpho-syntax, sociolinguistics, classification, phonetics/phonology, pragmatics, etc.). Reach out to and collaborate with native speakers in various languages. Communicate results of linguistic analyses to engineers and research scientists.

Requirements: Skills Must have strong written and spoken communication skills, especially business and research communication.

Must have: Near-native or native proficiency in a language other than English, more specifically a language of the following families or groups: Dravidian or Bantu (Swahili is a plus); Near-native or native proficiency in English. Working knowledge in other languages is a plus. Proficiency in a low-resource language is valued. Must be able to code in Python (must) and query databases using SQL, other coding languages used for data analysis are a plus. Must be able to independently work through complex requests and perform under pressure. Strong ability to work independently, prioritize, plan, and track work, as well as report progress education or training in the basics of project management is a plus self-motivation is a must Working knowledge of international language-classification standards is valued. Education PhD in Linguistics or related field is a must be finished (not in progress) a background or specialisation in corpus linguistics is a plus experience with field work is a plus a graduate degree in Literature or English is not an appropriate substitution degree in Computer Science with a specialisation in NLP is not an appropriate substitution Must have a very firm grasp of the following linguistic fields: language typology, syntax, morphology, sociolinguistics (especially dialectology and discourse analysis), corpus linguistics, writing systems, pragmatics, phonology. Must have some experience with applying basic Natural Language Processing techniques.

Experience Years of experience: 0-3 Experience working cross-functionally Experience collaborating with machine learning, NLP, or software engineers, or data scientists Experience contributing to research papers

Important: Preferably no known conflicts of interest in the fields of machine translation, ASR, TTS, or LLM research (as FAIR Linguists need to be contributing to research papers) Benefits Competitive salary Healthcare contribution and inclusion in company pension scheme Work laptop and phone 25 days annual leave (pro-rata) plus paid bank holidays Expanding workforce with potential for career progression for top performers.