Linguist

Job Description: Onsite ( hybrid) in Redmond, WA or Burlingame, CA Start/End Dates: 10/26/2026 - 4/25/202 (6 months - potential extension) The main function of a Linguist is to determine speech data needs and setting strategic vision for data-based model and product improvements. Job Responsibilities: Provide linguistic expertise in the areas of phonetics, phonology, lexicography, dialectology, and NLP. Design and conduct experiments for evaluating transcription quality. Develop manual and automated processes for multiple concurrent projects including ensuring high-quality label alignments, prosodic classification, POS identification and disambiguation, targeted modeling data, and user feedback. Create and perfect text normalization and inverse text normalization processes. Manage lexical and phrasal transcriptions and related metadata. Analyze system metrics such as user opinion, lexicon transcription coverage, and POS tagger performance and remedy pain points. Skills: Knowledge of phonetics, phonology, sociolinguistics, dialectology and other areas of linguistics. Ability to analyze waveforms and spectrograms. Knowledge of prescriptive writing and punctuation conventions for at least one language. Excellent communication skills both verbal and written. Knowledge in transcription and annotation systems such as SAMPA, IPA and ToBI. Education/Experience: Bachelor’s degree in linguistics, language technologies, computational linguistics, speech science, or related field. Must have skills: Foundational linguistics background — a BA/MA/PhD in linguistics, with applied linguistics knowledge (phonetics, phonology, familiarity with spoken vs. written forms). A linguistics background is required; a purely data science or engineering background is not a substitute. Technical skills — SQL and Python. Technical writing — able to produce clear guidelines, documentation, and analysis write-ups. Nice to have skills: Computational linguistics / ASR experience — quality evaluation using WER/CER/SER, dataset creation and quality assessment (both commissioned and synthetic), ideally some understanding of contextual biasing. Human grading operations — hands-on grading of data, writing guidelines, and training annotators. Experience with both offline/synthetic data and live traffic quality evaluation for voice assistants. #J-18808-Ljbffr