Job Description

Job Responsibilities:

• Develop annotation guidelines
• Work with tooling engineers to develop and debug new annotation workflows.
• Extract actionable quantitative and qualitative insights from user traffic on a regular basis.
• Scale these annotation processes as we expand new features, new locales, and new devices.
• Collaborate with other linguists to ensure weekly deliverables are met.
• Work under tight timelines while overcoming occasional tooling challenges and data ingestion issues.
• There are several Linguist roles currently open with Manager. This role does not require any specific languages and will not handle any objectionable content.
• Provide linguistic expertise while delivering data for large language models.
• Collaborate with other linguists and data operations teams in data collection, data curation, and annotation efforts.
• Evaluate and curate data sets for ML models using LLM solutions.
• Assess model performance and data quality.
• Prompt engineering.
• Create guidelines in support of labeling projects that enable annotators to consistently label language data at quality.
• Collaboratively develop complex and consistent linguistic analyses.

Skills:

• Knowledge of regular expressions, SQL, and Python.
• Excellent technical writing and communication skills both verbal and written.
• Critical thinking and problem-solving abilities.
• Understanding of a digital assistant’s technical stack (ASR, Understanding, Entity Recognition, etc.).
• Understanding of a digital assistant’s feature set (Weather, Reminders, Chatbot, Calling, Messaging, etc.) and how they coexist together.
• Resilient to technical setbacks out of your control.
• Fast learner.
• Proficiency/Familiarity in Python.
• Querying in SQL.
• Working autonomously - demonstrated ability to run their own project.
• Experience working directly with engineering partners - supporting the building of LLMs, prompt engineering.
• Experience auditing data - create guidelines for data.

Education/Experience:

• Bachelor’s degree in linguistics, language technologies, computational linguistics, speech science, or related field.

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