Linguist III

Job Title: Linguist III Duration: 04 Months (Possible extension) Location: Remote role. West coast preferred (cannot be located in TX or Illinois as those 2 states have passed laws that are incompatible with our data collection agreements) Summary: Must have a PhD in Linguistics IN HAND. Not just working to get one. A graduate degree in Literature or English is not an appropriate substitution. A degree in Computer Science with a specialization in NLP is not an appropriate substitution. A degree in Computational Linguistics is not the same as theoretical Linguistics. Must have near-native or native bilingual proficiency in a language from the Dravidian family and professional fluency from the Indo-Aryan family. (Candidates that don't meet the SPECIFIC language requirement will be disqualified. We're looking for a specific language family here). Dravidian is more of a focus here and being fluent in both 1 Dravidian and 1 Indo-Aryan language is the best profile. Please make sure the resume is CLEAR on which language the candidate is being submitted with and the CEFRL level. Top 3 must-have HARD skills: Perform linguistic error analysis of machine translations and identifying the most frequent and severe error categories Strong skills in pattern recognition, cross-functional communication, and multitasking Experience with Python Good to have skills: Experience with creating and/or maintaining specialized lexical resources (e.g., profanity dictionaries) a plus Ability to independently work through ambiguous requests, based on priorities established by CWAM, and perform under pressure. Able to work cross functionally. Main duties: 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. Skills: Must have strong written and spoken communication skills, especially business and research communication. Must have near-native or native bilingual proficiency in a language other than English, more specifically a language of the following families or groups: Dravidian or Indo-Aryan. 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: Graduate degree in Linguistics or related field is a must; PhD is a plus a background or specialization in corpus linguistics is a plus experience with field work is a plus 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) Compelling Story & Candidate Value Proposition: Here are some examples of the cool big things the FAIR C&L Linguistics team has provided impactful support for: NLLB (pivotless text-based translation system for 200 languages), now UNESCO's Universal Translator (spaces/UNESCO/nllb ) and one of the top translation engines on Wikipedia for low-resource languages. The research was published in Nature (articles/s41586-024-07335-x). MMS (ASR and TTS for over 1,000 languages), now UNESCO's ASR system (spaces/UNESCO/MMS ) in support of the Decade of Indigenous Languages, as well as, more recently, Omnilingual ASR (blog/omnilingual-asr-advancing-automatic-speech-recognition/ ), which supports over 1,600 languages and enables simple zero-shot additions. Seamless (pivotless speech-based translation system for 100 languages), which was recognized as one of Time's best 2023 AI inventions (collections/best-inventions-2023/6326994/meta-seamlessm4t/ ). The research was recently published in Nature (articles/s41586-024-08359-z#group-1 ).