Computational Linguist

Apple • Cupertino, CA

6d

About The Position

Join Apple's Entity and App Resolution team, where we build the intelligent
systems that help customers find and interact with exactly what they're looking
for. Our work powers personalized search and resolution capabilities that
improve user experiences. We're seeking a Computational Linguist to support our
entity resolution systems through data-driven work. In this role, you'll help
construct, generate, annotate, maintain, and analyze the data that power our
products. You'll help build processes and pipelines to streamline data
workflows. You will also be responsible for documenting and communicating
processes, guidelines, and findings. You'll work across engineering, quality,
localization, and UX teams, applying your linguistic expertise to ensure our
systems work well across different contexts and locales. Your systematic and
organized approaches will help to increase efficiency within and across teams.

DESCRIPTION

Data Generation & Management: Design, generate, and maintain high-quality
datasets for entity resolution testing and evaluation; automate data generation
pipelines where possible Annotation Projects: Plan, manage, and execute
annotation projects; create annotation guidelines, coordinate with annotators,
ensure quality and consistency Data Analysis: Clean, process, and analyze
language data using linguistic expertise to identify patterns, edge cases, and
system failures; surface insights that drive product improvements
Cross-Functional Collaboration: Work closely with Quality Engineering, UX
researchers, engineers, and localization teams to ensure entity resolution meets
quality standards and user needs Localization Awareness: Work with
internationalization to identify and address language-specific and cultural
issues in entity resolution across different locales Testing & Evaluation:
Design systematic test cases and evaluation frameworks; analyze test results to
identify linguistic patterns in failures Documentation: Create clear,
comprehensive documentation of scope, datasets, processes, findings, and
recommendations for diverse audiences

Requirements

• Master's degree in Linguistics, Computational Linguistics, or related field
• Strong data skills: cleaning, processing, analyzing, and finding patterns in language data
• Strong analytical skills: Experience with quantitative and qualitative data analyses
• Coding skills (e.g. Python, R) for the purpose of data processing and analysis
• 3-5 years of industry experience
• Experience with linguistic annotation
• Excellent communication skills and ability to work cross-functionally
• Strong organizational skills and documentation practices
• Systematic thinking and attention to detail
• Basic understanding of machine learning concepts

Nice To Haves

• Familiarity with version control (Git or similar)
• Familiarity with conversational systems, NLP, or search systems
• Experience managing or participating in annotation projects
• Experience with localization or multilingual issues in language technology
• Project management experience (academic or professional)
• Experience working with engineers or technical teams

Responsibilities

• Design, generate, and maintain high-quality datasets for entity resolution testing and evaluation
• Automate data generation pipelines where possible
• Plan, manage, and execute annotation projects
• Create annotation guidelines, coordinate with annotators, ensure quality and consistency
• Clean, process, and analyze language data using linguistic expertise to identify patterns, edge cases, and system failures
• Surface insights that drive product improvements
• Work closely with Quality Engineering, UX researchers, engineers, and localization teams to ensure entity resolution meets quality standards and user needs
• Work with internationalization to identify and address language-specific and cultural issues in entity resolution across different locales
• Design systematic test cases and evaluation frameworks
• Analyze test results to identify linguistic patterns in failures
• Create clear, comprehensive documentation of scope, datasets, processes, findings, and recommendations for diverse audiences

What This Job Offers

• Job Type: Full-time
• Career Level: Mid Level