Engineering Project Manager - AI Features Internationalization, L&RE

Benefits

Parental leave

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Non-birth-parent leave

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Family-building benefits

• Fertility benefits: Not verified
• Adoption assistance: Not verified
• Surrogacy assistance: Not verified

Mental health support

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Relocation assistance

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Childcare support

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Learning budget

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Verification

Not verified last checked Jun 13, 2026

Salary

$142K-$259K not verified - source not recorded; timestamp not recorded

401(k) match

Listed Source: EMPLR_CONTRIB_INCOME_AMT. source Last checked Jun 13, 2026.

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Market context

U.S. role benchmark (BLS OEWS)

$111,944 U.S. median for this role

Projected growth (BLS Employment Projections)

+13.7% - Much faster than average

79% above the BLS role benchmark for data and ml aggregate.

Matched to SOC 15-1252 - Data and ML aggregate by role bucket.

Source: U.S. Bureau of Labor Statistics, OEWS, May 2024 and Employment Projections, 2024-2034.

Schedule

Shift type

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Weekend work

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Application

Cover letter

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Assessment

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Deadline

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Where they hire

State eligibility is not yet verified.

About this role

Engineering Project Manager - AI Features Internationalization, L&RE Cupertino, United States of America Apple's Software Engineering Operations (SWE Ops) organization is seeking a highly technical Engineering Project Manager (EPM) to drive the internationalization and global launch of AI-driven products, including Apple Intelligence and new hardware with integrated ML capabilities. In this role, you will lead the technical integration of generative AI and machine learning features across 25+ languages and 40+ countries. You will sit at the critical intersection of Core ML Modeling, Data Science, Hardware Engineering, and Global Product Readiness. You are not just managing localization work-you are managing the technical dependencies, data pipelines, and model evaluation required to ensure Apple's AI features perform with high accuracy, safety, and cultural relevance worldwide. You will be responsible for the end-to-end execution of international features, from initial data collection and model evaluation to final software and hardware integration. AI Feature Orchestration: Facilitate deep technical coordination between Core ML, Software Engineering, Hardware Engineering, and Product Design to integrate AI features into international locales across software and hardware products. End-to-End Schedule Management: Produce and manage the master schedule for i18n deliverables, ensuring all cross-functional dependencies-from model training and fine-tuning to UI implementation and hardware readiness-are aligned for global launch. AI Data Operations: Direct the lifecycle of international data generation. Lead timelines for data collection, seek budget approvals for global datasets, coordinate with data collection teams and vendors, and iterate on "data playbooks" to improve model evaluation across diverse languages and regions. Model Evaluation and

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