Apples Software Engineering Operations

Apple Inc.
United States
11 days ago

Role details

Contract type
Permanent contract
Employment type
Full-time (> 32 hours)
Experience level
Expert
Experience required
5 years minimum
Working hours
Regular working hours
Languages
English

Tech stack

Training Data Artificial Intelligence Computer Vision Big Data Computer Engineering Data Files Design of User Interfaces Human-Computer Interaction Python (Programming Language) Machine Learning Language Modeling Natural Language Processing
+11 more
DataOps Software Engineering SQL Databases Systems Integration Scripting Large Language Models Model Validation Functional Dependencies Data Management Data Pipelines Data Generation

Job description

Apples 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 Apples 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 Quality: Drive international model evaluation strategy across audio, vision, language, and fusion models. Ensure eval coverage exists for target markets and identify performance gaps that could impact the customer experience internationally.

Hardware-Software AI Integration: Drive international readiness for AI features that span hardware, on-device ML, and companion software-coordinating across hardware engineering, NPS, and regional QA teams for new product introductions (NPI).

Technical Risk and Mitigation: Proactively identify and mitigate risks unique to global AI, such as linguistic bias, cultural representation gaps in vision models, regional model performance degradation, and data collection constraints in international markets.

Requirements

Stakeholder Leadership: Navigate complex internal organizations to surface risks, drive decisions on feature-by-country gating, and provide clear status to executive stakeholders across engineering, product marketing, and program leadership.5+ years of experience as an Engineering Program/Project Manager (EPM), Technical Program Manager (TPM), or similar technical leadership role within a software or hardware engineering organization.

Technical Lifecycle Mastery: Proven track record of managing the end-to-end development lifecycle for complex, multi-team features spanning software and hardware.

Cross-Functional Leadership: Demonstrated ability to manage complex dependencies across backend engineering (Modeling/Core ML), front-end implementation, hardware, and QA teams across multiple organizations.

International Product Expertise: Direct experience shipping products globally, with a deep understanding of internationalization (i18n) and the architectural and data challenges of scaling AI features for global markets.

Navigating Ambiguity: Ability to drive projects independently, make sound technical decisions with incomplete information, and influence teams without direct authority.

Communication: Ability to translate highly technical AI/ML concepts into clear, “lightweight” executive-level status updates and risk assessments.AI/ML Domain Depth: Hands-on experience driving AI/ML feature work, including familiarity with Large Language Models (LLMs), vision models, Natural Language Processing (NLP), or model evaluation frameworks.

New Product Introduction (NPI): Experience with international launch of hardware products containing ML/AI capabilities, including hardware access restrictions, data collection logistics, and field testing approvals.

Data Pipeline Management: Experience managing large-scale data generation, annotation, and evaluation workflows specifically for non-English locales and diverse cultural contexts.

i18n Engineering Standards: Technical knowledge of internationalization standards (e.g., Unicode, CLDR) and the architectural challenges of scaling models globally.

Fairness and Inclusion: Experience with demographic representation in ML training data and evaluation, including cultural and religious diversity considerations.

Budget and Resource Strategy: Experience managing significant budgets for international data acquisition and coordinating with global data vendors.

Analytical Proficiency: Ability to use data tools (e.g., SQL, Python, or internal dashboards) to track model performance, project health, and other analytics.

Skills: Acceptance Testing, Analysis Skills, Apple, Architectural Services, Artificial Intelligence (AI), Budget Management, Budgeting, Computer Engineering, Cross-Functional, Customer Experience, Data Collection, Data Management, Data Modeling, Data Science, Data Sets, Diversity, Engineering, English Language, Field Trials, Hardware Quality Assurance, Hardware-Software Integration, Internationalization, Lead Generation, Leadership, Localization, Logistics, Machine Learning, Modeling Languages, Natural Language Processing (NLP), Outbound Marketing, Performance Analysis, Performance Modeling, Product Design, Product Lifecycle, Product Marketing, Product Programs, Product Shipments, Product/Service Launch, Project/Program Management, Python Programming/Scripting Language, Quality Assurance, Reporting Dashboards, Risk, Risk Analysis, Risk Management, SQL (Structured Query Language), Sales Pipeline, Schedule Development, Software Engineering, Software Evaluation, Target Marketing, Technical Leadership, Training Data Sets, Unicode, User Interface/Experience (UI/UX), Workflow Analysis

About the company

Apple Inc

We bring amazing people together to make amazing things happen.

We’re a diverse collection of thinkers and doers, continually reimagining what’s possible to help us all do what we love in new ways. The people who work here have reinvented entire industries with the Mac, iPhone, iPad, and Apple Watch, as well as with services, including iTunes, the App Store, Apple Music, and Apple Pay. And the same passion for innovation that goes into our products also applies to our practices - strengthening our commitment to leave the world better than we found it.

About Apple

There’s a place here for every kind of brilliant. Everyone here is an innovator, or an innovator-to-be, no matter what your team or your role. So bring your passion, courage, and original thinking and get ready to share it, because every new product, service, or feature we invent is the result of people working together to make each others’ ideas stronger. Innovation at this level depends on people who represent the variety of the human experience and inspire us with their own fresh perspectives. Together, we’ll do amazing work that can make a difference in people’s lives. Including your own. Learn more about working at Apple.

Company Size: 10,000 employees or more

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