Linguist II

Job Title: Linguist II

Location: Onsite – 3 days in one of the following preferred offices:
Sunnyvale CA, New York NY, Burlingame CA, Washington, or Redmond WA.

Duration: 12 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. Candidates should possess solid linguistic data analysis skills, programming familiarity, and experience in language technology to contribute to data collection, synthetic data generation, and annotation tasks supporting LLM/AI training, evaluation, alignment, and AI agent development.

• 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 for model training and fine-tuning.
• Contribute to the development and maintenance of annotation schemas and guidelines for LLM training data (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‑team testing, and linguistic error analysis.
• Participate in experiments to assess data quality, annotation consistency, and downstream model performance.

• Bachelor's degree in Linguistics, Computational Linguistics, Computer Science, Speech Science, or a related field.
• 1+ years of experience in Linguistics, Language Technologies, NLP, or AI/ML data operations (or equivalent).
• Knowledge of syntax, semantics, pragmatics, sociolinguistics, corpus linguistics, and related areas.
• Familiarity with 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 (SQL, 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.

• Native or near-native fluency in English and at least one additional language.
• Master'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.
• Strong organizational skills and attention to detail.

• 1+ years of experience in Linguistics, Language Technologies, NLP, or AI/ML data operations (or equivalent).
• Knowledge of syntax, semantics, pragmatics, sociolinguistics, corpus linguistics, and other areas of linguistics.
• Familiarity with 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, spreadsheets, R, Unix, or others).

• Native or near-native fluency in English and at least one additional language.
• Master'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.
• Strong organizational skills and attention to detail.
• Experience working with speech and text data in multiple languages.
• Comfortable working in a fast-paced, highly collaborative environment with evolving priorities.