Linguist

Posted today

pri globalUnited (WV)

Data Scientists Translation and Interpretation Services

SENIORITY

Senior

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About the role

Job Description: Linguist IIRemote12 months We are looking for a linguist to help develop language components for AI-powered products, including large language models (LLMs) and voice-enabled technologies. We are seeking candidates with solid linguistic data analysis skills, programming familiarity, and language technology experience to contribute to data collection, synthetic data generation, and annotation tasks in support of LLM/AI training, evaluation, alignment, and AI agent development.

Job Responsibilities:

Apply linguistic expertise in syntax, semantics, pragmatics, and sociolinguistics to support LLM and generative AI Systems
Collaborate with linguists, data operations teams, and ML engineers on data collection, curation, annotation, and localization efforts for model training and fine-tuning
Contribute to the development and maintenance of annotation schemas and guidelines for LLM training data (e.g., instruction-tuning, preference labeling, RLHF)
Evaluate and quality-check datasets used for pre-training, fine-tuning, and alignment of language models
Support the development of programmatic methods for generating synthetic annotated data at scale
Assist in model evaluation efforts including prompt-based testing, red-teaming, and linguistic error analysis
Contribute to AI safety and responsible AI practices through linguistic review of model outputs (e.g., hallucination detection, bias identification, tone and pragmatic appropriateness)
Participate in experiments to assess data quality, annotation consistency, and downstream model performance

Required Skills:

Native or near-native fluency in English and at least one additional language
Knowledge of syntax, semantics, pragmatics, sociolinguistics, corpus linguistics, and other areas of linguistics
Familiarity with Large Language Models (LLMs), their applications and data practices (training data, evaluation, prompting, fine-tuning)
Exposure to LLM evaluation methodologies (human evaluation, automated metrics, adversarial testing)
Experience working with semantic ontologies, taxonomies, or intent/slot frameworks
Proficiency using AI Agents/Chatbots
Experience with database queries and data analysis processes (SQL, Python, spreadsheets, R, Unix, or others)
Experience working with speech and text data in multiple languages
Comfortable working in a fast-paced, highly collaborative environment with evolving priorities
Nice-to-have SkillsMaster's degree in Linguistics, Computational Linguistics, Language Technologies, or a related field
Familiarity with machine learning frameworks, NLP libraries, and tools (e.g., Hugging Face, spaCy, NLTK, PyTorch)
Exposure to statistical language modeling or training data pipelines

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