Linguist III

Job Title: Infrastructure Engineering - Linguist III

This role involves deep linguistic analysis and AI model evaluation within a dynamic infrastructure engineering team.

Main Duties

• Perform linguistic analyses on large datasets to identify patterns and errors.
• Analyze AI model outputs for linguistic inaccuracies and categorize findings systematically.
• Develop and refine guidelines for annotation processes and AI project requirements.
• Conduct in-depth linguistic research comparing language similarities and differences across various languages.
• Analyze language for Responsible AI issues, including bias and toxicity, in multilingual settings.
• Review and summarize relevant linguistic literature, focusing on Natural Language Processing (NLP) applications.
• Compare the quality of different vendor outputs and provide feedback on recurring error patterns.
• Offer expert linguistic guidance and support to project teams.
• Collaborate effectively with native speakers to ensure linguistic accuracy and cultural relevance.
• Communicate complex findings clearly to engineers and scientists.

Skills Required

• Excellent written and spoken communication skills, suitable for both business and research environments.
• Native proficiency in a non-English language (preferably Hindi) with strong skills in an Indo-Aryan or South Dravidian language, and a broad understanding of other languages within these groups.
• Proficiency in a low-resource language is highly valued.
• Required proficiency in Python coding and SQL querying. Knowledge of other data analysis languages is a plus.
• Demonstrated ability to work independently on complex tasks under pressure.
• Exceptional prioritization, planning, tracking, and reporting capabilities.
• Basic project management understanding is beneficial.
• Required self-motivation and a proactive approach to work.
• Valued working knowledge of international language-classification standards.

Education Requirements

• A graduate degree in Linguistics or a closely related field is mandatory; a PhD is advantageous.
• Specialization in corpus linguistics is a plus.
• Fieldwork experience is considered a benefit.
• Degrees in Literature or English are not considered appropriate substitutions.
• Computer Science degrees with an NLP specialization are not appropriate substitutions for this role.
• Essential: Strong knowledge of language typology, syntax, morphology, sociolinguistics (including dialectology and discourse analysis), corpus linguistics, writing systems, pragmatics, and phonology.
• Required experience with fundamental Natural Language Processing techniques.

Experience

• 0-3 years of relevant professional experience.
• Experience working collaboratively across different functional teams.
• Experience partnering with Machine Learning (ML), NLP, software engineers, or data scientists.
• Proven track record of contributing to research papers.
• Preferably, candidates should have no known conflicts of interest related to machine translation, ASR, TTS, or LLM research.

Key skills/competency

• Linguistics
• Natural Language Processing (NLP)
• Python
• SQL
• Data Analysis
• AI Model Evaluation
• Responsible AI
• Language Typology
• Corpus Linguistics
• Machine Learning