Linguistic Engineer Responsibilities:
Provide linguistic expertise in the areas of syntax, semantics, pragmatics, dialog, ontology, and other NLP areas (such as ASR or TTS).
Clearly communicate expertise with project stakeholders.
Identify best practices and improve procedures across NLP systems.
Identify linguistic needs and gaps within project ontologies and NLP systems.
Anticipate language-based problems before they occur.
Drive projects from conceptualization through launch and beyond with continual improvement and support.
Design and conduct language experiments.
Deliver artifacts for project components that improve a language solution, impacts maintainability and scalability of language systems.
Identify opportunities to improve user experiences with NLP features.
Degree in Linguistics, Language Technologies, Computational Linguistics, Speech Science, related field, or equivalent industry experience.
Experience in various areas of linguistics, including phonetics, phonology, morphology, syntax, semantics, pragmatics, discourse analysis, sociolinguistics, psycholinguistics, computational linguistics, and field work.
Experience designing and conducting language data experiments.
Experience with hierarchical structures and ontologies.
Experience with text labeling problems.
Experience prioritizing multiple work streams and conducting day-to-day tasks without oversight.
Track record working on or leading cross-functional efforts, initiatives, or projects.
Experience forming internal team relationships and fostering external relations.
Advanced degree in Linguistics, Language Technologies, Computational Linguistics, Speech Science, or related field.
Experience with larger scripting projects that involve combining language data from different sources, computing complex metrics over large datasets, etc.
Strong understanding of the relationship between data and machine learning models in order to increase linguists’ impact on ML projects.
Familiarity with core data processing techniques and tooling (including version control, unit tests, and other programming best practices).
Experience with a product development/release cycle, quality control, and continuous improvement strategies.
Experience with responsible AI approaches, enabling and preserving privacy, integrity, and fairness.
Demonstrated leadership within smaller projects or teams.
Fluency in two or more natural languages.
2+ years relevant industry experience.
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