Apple has 261 active AI-related job listings. The majority of these roles are focused on agents, accounting for 24% of the total, followed by application (22%) and serving infrastructure (21%). Engineering is the primary function for these positions, with the United States being the dominant hiring country. Frequent tech tags include model serving, inference infrastructure, and LLM observability. Over the last 30 days, Apple has posted 111 new AI roles, representing a 61% increase compared to the previous 30-day period.
Currently tracking 171 active AI roles, down 37% versus the prior 4 weeks. Primary focus: Agent · Engineering. Salary range $120k–$487k (avg $235k).
Apple currently has 233 active AI-related roles in our index. The most common open titles are: Machine Learning Engineer (4), AIML - Sr Data Scientist, Evaluation (2), Advanced Manufacturing Engineer(iPhone) - Smart Manufacturing (2), Machine Learning Engineer, Apple Services Engineering (2), Machine Learning Software Engineer (2). Most positions are in Engineering and Research.
Apple's active AI hiring is concentrated in: agents (30%), application (21%), serving infrastructure (14%). These categories follow a seven-stage AI lifecycle: data, pre-training, post-training, serving infrastructure, agents, evaluation, and application.
Apple is hiring AI talent in: United States (182 roles), China (17 roles), India (10 roles), United Kingdom (7 roles).
Job postings at Apple most frequently mention: Machine Learning, Python, Data Science, Large Language Models (LLMs), Statistics.
In the past 30 days, Apple has posted 80 new AI-related roles.
| Title | Stage | AI score |
|---|---|---|
| Machine Learning Engineer - Intern Research-focused ML Engineer Intern at Apple's AI/ML org, focusing on data curation, model evaluation, and exploring new ML methods for large-scale systems, computer vision, NLP, and multi-modal understanding. The role involves collaborating with researchers and engineers to develop transformative products and publish groundbreaking research. | DataPost-train | 9 |
| Senior Engineering Manager, Apple Data Platform Senior Engineering Manager to lead a team building foundational systems and services for Apple's AI and Data governance platform. The role focuses on Big Data management, ML infrastructure, and Generative AI, enabling efficient and scalable model development while ensuring compliance with AI regulations. The manager will influence how ML practitioners develop and scale models across Apple's products and services. |
| DataPost-train |
| 8 |
| AIML - Sr Machine Learning Engineer, Data and ML Innovation Machine Learning Engineer at Apple focused on innovating and applying state-of-the-art ML research to complex data problems, specifically for Apple Intelligence. The role involves designing and developing a data generation and curation framework for foundation models, building evaluation pipelines, and exploring new methods for synthetic data creation across vision, text, and audio. The position also emphasizes collaboration with multidisciplinary teams and potentially publishing research. | DataPost-train | 8 |
| Senior Privacy Engineer, Intelligence (User Privacy) Senior Privacy Engineer focused on providing privacy guidance for machine learning and generative AI infrastructure at Apple. This role involves reviewing features, auditing products, guiding the roadmap of privacy technologies like differential privacy and private federated learning, and developing privacy-preserving data collection methodologies for AI systems. | DataPost-train | 7 |
| Engineering Leader, Data Engineering Engineering leader to build and lead a data engineering organization responsible for massive-scale data pipelines and services for Apple's Media Services. The role involves architecting systems for an AI-first paradigm, producing ML-ready data, and leading technology modernization programs. | Data | 7 |
| Americas Business Process Re-Engineering Data Engineer Data Engineer role focused on building and maintaining scalable data infrastructure for analytics, machine learning, and AI-driven decision-making within Operations. The role involves designing data pipelines, building data models, implementing data observability, and collaborating with data science and ML engineering teams. It also emphasizes leveraging AI-assisted tools for development and researching emerging GenAI data tooling. | DataAgent | 7 |
| Senior Manager - AI Data Operations The Senior Manager of AI Data Operations will lead an organization of internal domain experts to build scalable annotation programs that balance accuracy and speed while maintaining quality standards. This role partners with Engineering, Data Science, and Programs to translate evolving system requirements into robust audit pipelines, tooling strategies, and measurable performance lift. Responsibilities include owning end-to-end data annotation and system audit operations, designing quality frameworks, operationalizing auditing for training, evaluation, and red-teaming, driving tooling evolution and automation strategy, and developing data augmentation strategies. | DataEval Gate | 7 |
| Senior Backend Systems Engineer, Sensing & Connectivity This role focuses on building backend systems for location intelligence, processing sensor data, and applying ML to extract insights. It involves owning the full ML lifecycle from problem formulation to production deployment, with a strong emphasis on software engineering and distributed systems at scale. | DataPost-train | 5 |
| Privacy Engineer - Systems Experiences, Apps, and Technologies This Privacy Engineer role at Apple focuses on designing and reviewing features and data collection methodologies to protect user privacy, particularly in the context of generative AI systems and fraud detection. The role involves guiding the development of data collection systems for training and evaluating AI, auditing products for privacy risks, and partnering with technical experts to build privacy-preserving features. | Data | 5 |
| Senior Maching Learning & Data Scientist, OS Power & Performance Senior Machine Learning & Data Scientist role focused on quantitative analysis of high-dimensional data to improve Apple's product performance. Responsibilities include producing metrics, models, and simulations, applying statistical analysis to product development, and writing production-level code. Requires a strong foundation in statistics, software engineering, and data engineering. | Data | 5 |
| Data Engineer Data Engineer role focused on building and maintaining high-volume data processing pipelines, ingestion, and ETL/ELT applications. The role involves applying Generative AI, RAG, and ML for anomaly detection to enhance data analytics capabilities, with a focus on cloud environments using technologies like Kafka, Spark, Flink, Docker, and Kubernetes. | DataAgent | 5 |
| Senior Data Engineer Senior Data Engineer for Apple's App Store team, focusing on designing and delivering privacy-centric data products, including pipelines and analytical outputs. The role involves architecting distributed pipelines, building self-service data platforms, and implementing GenAI-driven observability. Collaboration with various Apple teams is key, and the ideal candidate has strong software engineering and data expertise. | Data | 5 |
| Software Engineer, Triage Intelligence and Debug Engineering, CoreOS Software Engineer role focused on Triage Intelligence and Debug Engineering within Apple's CoreOS. The role involves improving and maintaining device management systems, collaborating with cross-functional teams, and potentially applying ML/AI techniques to systems problems like crash clustering and log anomaly detection. Familiarity with LLMs and generative AI tooling is preferred. | Data | 5 |
| Software Development Engineer - Ads Delivery Software Development Engineer to build highly scalable platforms and services for Apple's Advertising Platforms group. Responsibilities include designing, implementing, and operating distributed and scalable services and data applications, building efficient data pipelines, and applying machine learning techniques to enhance ad targeting and measurement. Requires strong experience in distributed systems, microservices, big data technologies, and cloud platforms. | Data | 5 |
| AIML Data Operations - Annotations Production Team Manager This role manages a team of crowd managers responsible for overseeing external vendor workforces that produce annotated data for AI/ML models. The focus is on vendor management, production operations, quality oversight, and scaling data annotation processes to meet Apple's AI innovation needs. | Data | 5 |
| Engineering Manager, App Store Data Engineering Manager for App Store's data engineering and analytics team, focusing on compliance-critical data products, pipelines, and analytical outputs. The role involves people leadership, technical guidance, and ensuring operational excellence while partnering with stakeholders to deliver scalable data solutions. Emphasizes AI-native development practices and LLM-augmented workflows across the SDLC, with a strong focus on data quality, governance, and compliance. | Data | 5 |
| Senior Manager of Quality Assurance, AIML Data Operations Senior Manager of Quality Assurance for AIML Data Operations at Apple. This role focuses on leading the QA function for data annotation pipelines that feed into AI/ML models. Responsibilities include defining quality standards, managing a team of QA professionals, developing scalable QA processes, and collaborating with Data Science and ML Engineering teams to ensure high-quality labeled data. The role requires a strong understanding of AIML concepts and practical experience in data quality assurance at scale. | Data | 5 |
| Sr. ML Infrastructure Engineer, Siri Runtime Systems and Interaction The role focuses on building the data and infrastructure ecosystem to support ML development for Siri. It involves end-to-end ownership of services and data products, working closely with ML Modeling, Infrastructure, Software, Hardware, and Operations teams. | Data | 5 |
| Sr. Machine Learning Infrastructure Engineer, Creator Studio This role focuses on building and maintaining scalable ML data infrastructure for creative editing tools, enabling high-quality ML model development. It involves sourcing multimodal datasets, building data pipelines, and supporting model development teams. | Data | 5 |
| Sr Full-Stack Software Engineer, AIML Data Operations This role is for a senior full-stack software engineer focused on delivering high-quality data for LLM training and evaluation. The engineer will build and operate custom internal software solutions, including data collection clients (Swift/web apps), web services, and large-scale distributed data-processing pipelines. The role is crucial for foundational AI development at Apple, contributing to products like Apple Intelligence and Siri. | Data | 5 |
| Sr Software Engineering Manager, AIML Data Operations Engineering Manager for AIML Data Operations at Apple, leading a team that builds software for machine learning data collection and delivery at scale. The role involves technical direction, team leadership, and collaboration with ML researchers and product teams. | Data | 5 |
| Data Scientist, AIML Data Scientist This role focuses on data operations and capacity planning within an AI/ML context, specifically analyzing annotator performance, task complexity, and data characteristics to optimize data annotation workflows and project scoping. The goal is to ensure high-quality annotated data for unreleased products and AI technology by improving efficiency and quality through data-driven insights and experimentation. | Data | 5 |
| Data Integration Engineer Data Integration Engineer responsible for building and maintaining data pipelines for structured and unstructured data to support AIML model development and deployment. Focuses on data infrastructure, data quality, and integration for sales processes. | Data | 5 |
| Human Factors Research Engineer, AIML Data Operations This role focuses on human factors research to optimize annotation workflows and analyst tools for machine learning data operations at Apple. The goal is to improve the quality and efficiency of human-annotated data used in AI initiatives, supporting products like Apple Intelligence and Vision Pro. | Data | 5 |
| Data Science Leader, AIML Data Operations This role leads a Data Science team focused on AIML Data Operations, establishing health metrics, identifying growth drivers, and recommending optimizations for high-quality annotated data to support unreleased AI products. The focus is on analytics, experimentation, and building cross-functional relationships to drive data-informed decisions. | Data | 5 |
