Engineering Project Manager, AI Features Internationalization

Apple Inc

Confirmed live yesterday High trust

Quick summary

Work type: On-site
Location: Cupertino, CA
Salary: $144,600–$263,800 / yr
Posted: 23 days ago
Freshness: Confirmed live yesterday
Nearby: 99+ roles within 25 mi

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Competitive pay

How this pay compares to similar roles

Similar $208k

This role $204k

$130k most similar roles pay here $278k

This role pays more than 51% of similar roles. Most pay $162,000–$253,775 — the shaded band above. At the midpoint, this role pays about $204k versus about $208k for comparable roles.

Based on 240 similar postings.

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About Apple Inc

Apple Inc. is a multinational technology company known for designing and manufacturing consumer electronics, software, and online services, including the iPhone, Mac, iPad, and App Store. Industry: Consumer Electronics & Software

Apple Inc currently has 1984 open roles on FindRole.

Listed pay typically runs $175,000–$277,600 across 1590 roles with salary data.

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At a glance

TL;DR · Engineering Project Manager, AI Features Internationalization

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The Engineering Project Manager - AI Features Internationalization joins the Software Engineering Operations team to lead the technical integration of generative AI and machine learning features across numerous languages and countries. This role involves managing complex technical dependencies, data pipelines, and model evaluation for products like Apple Intelligence and hardware with integrated ML capabilities. You will coordinate between Core ML Modeling, Data Science, Hardware Engineering, and Product Design to ensure high accuracy and cultural relevance. Key responsibilities include overseeing international data generation, managing master schedules for i18n deliverables, and mitigating risks such as linguistic bias or regional performance degradation. The role requires expertise in Large Language Models, vision models, Natural Language Processing, and evaluation frameworks. You will utilize tools like SQL and Python to track model performance while navigating the architectural challenges of scaling AI features globally.

Skills

Machine Learning Core ML Large Language Models NLP Python SQL Data Pipelines i18n Unicode CLDR NPI Model Evaluation Hardware Engineering Software Engineering

What you'll do

Coordinate technical integration of generative AI and machine learning features across 25+ languages and 40+ countries.
Manage the master schedule for internationalization deliverables, including model training, fine-tuning, and hardware readiness.
Direct the lifecycle of international data generation, including budget approval and vendor coordination for global datasets.
Drive international model evaluation strategies across audio, vision, and language models to ensure high performance in target markets.
Manage technical dependencies between Core ML, software engineering, hardware engineering, and product design teams.
Identify and mitigate risks related to linguistic bias, cultural representation gaps, and regional performance degradation.
Coordinate the integration of AI features across hardware, on-device ML, and companion software for new product introductions.
Communicate complex technical AI/ML status updates and risk assessments to executive stakeholders.

What we're looking for

5+ years of experience as an Engineering Program/Project Manager, Technical Program Manager, or similar technical leadership role.
Proven track record managing the end-to-end development lifecycle for complex features spanning software and hardware.
Demonstrated ability to manage cross-functional dependencies across backend engineering, front-end implementation, hardware, and QA teams.
Experience shipping products globally with a deep understanding of internationalization (i18n) and scaling AI features for global markets.
Ability to drive projects independently and make technical decisions with incomplete information while influencing teams without direct authority.
Ability to translate complex AI/ML concepts into clear executive-level status updates and risk assessments.
Hands-on experience driving AI/ML feature work, including LLMs, vision models, NLP, or model evaluation frameworks (preferred).
Experience with New Product Introduction (NPI) for hardware products containing ML/AI capabilities (preferred).

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