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 |
|---|---|---|
| Senior Apps Applied Scientist This role focuses on designing, developing, and implementing sophisticated machine learning and AI models for creative applications, particularly image editing apps. It involves building end-to-end ML pipelines, prototyping AI features, developing AI tools, and deploying models into production. The role requires strong Python programming, experience with large-scale data, causal inference, LLM fine-tuning, RAG, and AI framework development. | Post-trainServe | 7 |
| Sr Technical Product Manager, AI & Data Platforms (AiDP) Senior Technical Product Manager for Apple's AI & Data Platforms team, focusing on building and launching GenAI capabilities for enterprise use cases like knowledge discovery, conversational AI, and workflow automation. The role involves defining product strategy, roadmaps, and user experiences, partnering with engineering and data science, and driving product delivery and adoption across Apple's business units. |
| Ship |
| 7 |
| Machine Learning Test and Automation Engineer, Graphics, Games, and ML The Machine Learning Test and Automation Engineer will design and build scalable test solutions for validating on-device and distributed Apple Intelligence inference, focusing on correctness, reliability, and performance of the inference runtime software. This role involves developing functional and performance tests within a CI/CD pipeline, partnering with ML engineering and infrastructure teams. | Serve | 7 |
| Senior Machine Learning Manager, Answers, Search & Knowledge Platforms This role manages a team focused on enhancing Siri and Apple products by advancing real-time augmented information retrieval and generation, knowledge graph engineering, and LLM-powered answer generation for user knowledge questions. It involves E2E knowledge graph construction, serving, and understanding user intent to deliver knowledge-driven user experiences. | AgentServe | 7 |
| Machine Learning Research Engineer, Camera & Photos Machine Learning Research Engineer focused on image processing pipelines and innovative algorithms for Apple's mobile devices (iPhone, iPad). The role involves leveraging research in image processing, statistics, and computer vision to design, develop, and improve imaging technologies, turning concepts into commercially viable algorithms for Apple's camera systems. | Ship | 7 |
| Senior Product Data Scientist in Causal Inference and ML, App Store Senior Product Data Scientist role focused on driving data-driven strategy and delivering ML and experimentation solutions for Apple's App Store. The role involves applying advanced ML causal inference techniques, developing and deploying ML models for customer insights, and leveraging LLMs/GenAI tools. It requires strong expertise in causal inference, experimentation frameworks, and influencing cross-functional roadmaps. | Agent | 7 |
| Machine Learning (MLOps) Engineer MLOps Engineer role focused on building and optimizing ML infrastructure, ensuring reliability, scalability, and continuous improvement of AI/ML systems in production. Responsibilities include end-to-end quality initiatives, automated pipelines for training, evaluation, deployment, and championing model observability and governance. | ServeEval Gate | 7 |
| Language Engineer (Swedish), Global Siri Language Engineer for Siri in Swedish, focusing on applying ML/NLP and LLMs to improve understanding and speaking of Swedish for Siri products. The role involves end-to-end user experience, data-driven analysis, implementing innovations, and working with LLM prompting and fine-tuning. | Post-trainServe | 7 |
| Language Engineer (Polish), Global Siri Language Engineer for Siri (Polish) responsible for end-to-end user experiences, applying ML and NLP techniques to deliver products, with a focus on developing, training, and fine-tuning LLMs for internationalization challenges in a large-scale consumer product. | Post-trainServe | 7 |
| ML Engineer - Evaluation Analysis, Metric and Data Strategy ML Engineer focused on defining and analyzing quality metrics for AI-powered features in consumer productivity and creative applications. This role is critical for informing model development, feature launches, and product strategy by translating evaluation data and user behavior into actionable insights. It involves designing metrics frameworks, auditing data representativeness, and developing evaluation methods for complex, agentic AI experiences. | Eval GateAgent | 7 |
| Siri, Eval Architect Engineer The role focuses on defining the architecture for systems that measure Siri's quality across platforms and model updates. It involves building evaluation infrastructure for large-scale automation, simulation, AI-powered auto-evaluators, and agentic fix pipelines. The Eval Systems Architect will own the technical vision and system architecture for Siri's evaluation stack, ensuring coherence, scalability, and trustworthiness, and will influence the technical roadmap for the evaluation platform. | Eval GateAgent | 7 |
| Video Machine Learning Engineer, Audio & Media Technologies Video Machine Learning Engineer at Apple, focusing on developing and integrating ML/DL solutions for video coding and processing in Apple products. Responsibilities include designing, training, optimizing, and integrating neural networks, as well as enhancing user experiences in video communication. Requires a Master's degree or equivalent experience in EE/CS, digital video processing, modern video codecs, and neural network design/optimization. | Post-train | 7 |
| On-Device ML Infrastructure Engineer (CoreML Runtime), Graphics, Games & ML This role focuses on building and maintaining the Core ML Runtime for on-device execution of ML models on Apple products. The engineer will work on the ML graph compiler, runtime, and kernels, optimizing model execution for performance, energy efficiency, and thermal management. The role involves developing production-critical system software for implementing ML models on Apple Silicon, with a focus on common compiler optimizations and runtime systems. | Serve | 7 |
| Computer Vision Software Engineer — Camera Technologies & Systems Develop and ship computer vision, image processing, and machine learning software features for Apple's camera technologies, impacting millions of iPhone users. | Ship | 7 |
| Test Triage & Automation Engineer, Siri This role focuses on designing, driving, and triaging automation pipelines and evaluation frameworks for Siri's AI features. The engineer will analyze large-scale test data, identify trends, and develop strategies to improve the efficiency and effectiveness of quality engineering processes. The goal is to ensure the qualitative experience of Siri's AI features meets high standards and to influence product decisions and model improvements. | Eval GateAgent | 7 |
| Sr. Software Engineer - Data, Siri Speech This role focuses on building and automating backend tools for Siri's Speech data warehouses, including cataloging, annotation, and making the data queryable via LLM-based chatbots. It involves distributed data engineering at the intersection of speech recognition, NLP, and dialogue management, with the goal of improving training and evaluation of Siri's models. | DataPost-train | 7 |
| Software Engineer, Siri Attention and Invocation Software Engineer role focused on the on-device platform for Siri's attention and invocation features, involving integration of ML models, performance optimization, and system-level architecture for multimodal machine learning solutions across Apple devices. | Serve | 7 |
| Software Engineer, Siri Attention And Invocation Software Engineer for Apple's Siri team, focusing on improving speech recognition, natural language understanding, and dialogue management through advanced statistical techniques and core machine learning algorithms. The role involves end-to-end feature development, collaboration with cross-functional teams, and shipping user-facing features to millions of users. | Post-trainAgent | 7 |
| Sr. Software Architect, Siri Attention and Invocation Senior Software Architect for Siri Attention and Invocation team, focusing on designing and implementing software systems for natural and conversational interactions with virtual assistants using AI/ML technologies, including LLMs and conversational AI. The role involves architecting ML-driven user experiences, integrating with sensory and system software, and optimizing on-device runtime performance. | Agent | 7 |
| Staff Machine Learning Performance Engineer, Siri Runtime Systems and Interaction Staff Machine Learning Performance Engineer for Siri, focusing on optimizing LLM and ML model inference stacks for performance and efficiency, involving on-device vs. server model decisions and collaboration with hardware/software teams. | Serve | 7 |
| Sr. Software Engineer, Siri Speech This role is for a Sr. Software Engineer on the Siri Speech team at Apple, focusing on delivering natural language capabilities using ML. The responsibilities include productizing new models for Apple hardware, designing inference systems, building cloud services, and optimizing performance. The role requires experience in iOS development, generative AI agents for coding, and production model inference, with familiarity with large language models preferred. | Serve | 7 |
| Machine Learning Engineer, Sensing & Connectivity Machine Learning Engineer at Apple to build next-generation features using multi-modal sensing, focusing on motion sensing and interactive technologies. Responsibilities include designing and implementing models & algorithms, optimizing for power, memory, and performance, developing data pipelines, and deploying efficient, low-power models for customer-facing products. | ServePost-train | 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 |
| Software Engineer, Frameworks/Data, Sensing & Connectivity Software Engineer focused on data collection, processing, and ML training data curation for on-device sensors and wireless technologies. The role involves building tools for data analysis, creating datasets for LLM benchmarking, and developing frameworks for evaluating generative AI output quality and reliability. It also includes designing data pipelines for sensor data and collaborating with teams to create intelligent experiences. | DataEval Gate | 7 |
| Software Engineer (Security) - AI & Data Platforms (AiDP) Software Engineer focused on building and managing internal security services that leverage AI technologies to identify and remediate security risks within the software development lifecycle. The role involves assessing AI-specific security risks and implementing controls, with a preference for experience in LLM-powered solutions. | Agent | 7 |
| Marcom Creative Technologist This role is for a Creative Technologist in Apple's Marcom team, focusing on R&D and prototyping of innovative experiences using emerging technologies like generative AI, LLMs, diffusion models, and agents. The role involves coding, research, experimentation, and collaboration to integrate these technologies into internal workflows and customer-facing experiences. | AgentData | 7 |
| 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 regulatory compliance. It involves leading efforts in data lake governance and GenAI infrastructure across the entire model development lifecycle, influencing ML practitioners and product development. | DataServe | 7 |
| Applied Scientist Applied Scientist role at Apple focusing on causal inference, statistics, and machine learning to optimize marketing channels for consumer services. The role involves designing, developing, and deploying solutions using observational testing, counterfactual modeling, and lifetime value estimation, working with large-scale, privacy-focused datasets. Key responsibilities include engineering end-to-end causal inference products, analyzing data for automation and modeling opportunities, collaborating with cross-functional teams, and staying updated on research advancements. | Ship | 7 |
| Reliability Engineer Software Engineer on the Applied Machine Learning Team to architect and orchestrate high-performance, scalable enterprise platforms for Data, ML, and inferencing. Focus on ensuring availability, performance, and low latency for high-throughput applications. Manage diverse workloads across ML/Data/Inference platforms and evaluate new technologies. | ServeData | 7 |
| AIML - ML Platform Engineer (Apple Ecosystem), Data Intelligence Platform This role focuses on building and shipping the ML platform and tools that enable product teams across Apple to develop and deploy machine learning solutions. The engineer will be responsible for the infrastructure, tools, and developing ML solutions, with a strong emphasis on scalability, reliability, and ease of use. | Serve | 7 |
| CI Systems Engineer (AI Failure Analysis), Developer Workflows This role focuses on building AI-assisted systems to analyze CI build and test failures, transforming raw data into actionable insights for OS engineers. The engineer will design and implement AI-powered workflows for failure summarization, pattern identification, and distinguishing signal from noise, integrating AI capabilities into developer tools to accelerate the software development process. | Agent | 7 |
| Product Manager — Generative AI, Ai & Data Platforms (AiDP) Product Manager for Generative AI within Apple's Ai & Data Platforms team, focusing on building and scaling GenAI capabilities for enterprise use cases like knowledge discovery, conversational AI, and workflow automation. The role involves defining product strategy, working closely with engineering and data science, and ensuring AI is trustworthy, governable, and reliable at scale. Requires a technical background, ability to prototype, and experience shipping AI/ML products. | Agent | 7 |
| AI Product Development Lead This role leads the product engineering and building efforts for AI-driven tools within a legal tech ecosystem, focusing on rapid development, prototyping, and delivering legal-contextualized AI applications and features embedded into existing legal workflows. The role involves managing a team, building upon internal AI platforms, and bridging the gap between AI capabilities and business needs. | AgentServe | 7 |
| Machine Learning Engineer, Strategic Data Solutions (Fulfillment, Supply Chain, Logistics domain exp) Machine Learning Engineer role focused on applying ML and optimization to supply chain and logistics problems for Apple's Fulfillment Operations team. The role involves designing, building, deploying, and maintaining end-to-end data pipelines and models to improve operational efficiency and security, with a focus on productionizing and owning the stack. | Ship | 7 |
| Machine Learning Engineer — Trust and Safety (Account Trust) Machine Learning Engineer focused on Trust and Safety for communication apps, protecting against spam and abuse. The role involves building ML tooling for the entire ML lifecycle, from data ETL and model training to evaluation and deployment, with a strong emphasis on anti-fraud and anomaly detection, particularly in the context of LLMs. The goal is to deliver reusable tooling and integrate with existing systems to enhance customer safety and mitigate attack vectors. | AgentData | 7 |
| AI Solutions Consultant – Innovation Lab This role is for an AI Solutions Engineer in Apple's Innovation Lab, focusing on helping enterprise customers build applications on Apple platforms using AI and Spatial Computing. The role involves consulting, architecting, building demonstrations, and evangelizing best practices for AI-powered enterprise applications. Requires expertise in LLMs, RAG, traditional ML, and Apple platform development. | Agent | 7 |
| Wi-Fi AI/ML Software Engineer, Wireless Technologies & Ecosystems This role focuses on applying AI/ML to Wi-Fi software for Apple products, optimizing performance, predicting congestion, and enhancing connection reliability. The engineer will design and implement ML models, apply AI to internal tools, analyze network data, and optimize models for on-device inference. The role involves collaboration with hardware and software teams, and a strong understanding of networking protocols and wireless standards is required. | ServeData | 7 |
| Senior Software Engineer, Applied Machine Learning
, Sensing & Connectivity Senior Software Engineer for Apple's Applied Sensing & Health team, focusing on delivering Health and Fitness features for Apple products. The role involves architecting and implementing C++ systems for sensor data processing, translating ML research into production algorithms, and maintaining system software with real-time constraints. Requires strong C++ skills, Python for ML, and understanding of ML pipelines. | ServePost-train | 7 |
| On-Device ML Infrastructure Engineer, ML User Experience, APIs & Integration, Graphics, Games & ML This role focuses on building the ML infrastructure and developer experience for running ML models on Apple devices. It involves developing APIs for ML model conversion and authoring, optimizing models for efficiency and performance, and integrating ML tools into repositories. The goal is to enable efficient ingestion and implementation of models within Apple's ML stack, impacting various core experiences like Camera, Siri, and Health. | Serve | 7 |
| On-Device ML Compiler Engineer, Model Compilation, Graphics, Games & ML This role focuses on building and optimizing ML compilers and runtimes for on-device execution across Apple's diverse hardware (Neural Engine, GPU, CPU). It involves working with MLIR-based compiler stacks to improve runtime performance and enable efficient execution of ML models on Apple devices, impacting core experiences like Camera, Siri, and Health. | Serve | 7 |
| On-device ML Infrastructure Engineer, Compiler & Runtime, Graphics, Games & ML Seeking an experienced ML Infrastructure Engineer to build and optimize the execution engine and compilation toolchain for on-device ML models on Apple products. This role focuses on creating efficient, portable, and extensible runtimes and compilers, connecting compiler technology, runtime components, kernel libraries, and hardware compilers to enable ML execution across various devices. | Serve | 7 |
| On-device ML Integration Engineer, Graphics, Games & ML This role focuses on integrating ML models into Apple's on-device inference stack, optimizing performance, and ensuring functionality across various Apple devices. It involves working with ML frameworks, compilers, and hardware targets to enable efficient and private AI experiences. | Serve | 7 |
| Applied Sensing & Health, Embedded Systems Engineer, Sensing & Connectivity Develops software for next-generation fitness, safety, and health experiences by transforming multi-modal sensor data into insights using advanced machine learning and foundation models, impacting millions of Apple Watch, iPhone, and AirPods users. | ShipPost-train | 7 |
| Senior Machine Learning Engineer – Ads Predictions Senior Machine Learning Engineer to join the Predictions group, focusing on building core ML models for ad predictions and monetization across Apple's App Store and News platforms. The role involves designing and implementing ML models for user interaction, CTR, and CVR prediction, developing retrieval algorithms, and contributing to modeling areas like deep neural networks, contextual bandits, multi-task learning, and LLM-based ranking signals. It also requires working with large-scale datasets, collaborating with cross-functional teams, and running experiments. Experience with ad tech, recommender systems, or web-scale search/retrieval is preferred, along with deep expertise in neural network architectures and training pipelines. | AgentServe | 7 |
| Swift LLM API Engineer, Swift Platform Experience This role focuses on building APIs for AI models within Apple's Swift Frameworks team. The engineer will implement features, design APIs, and be involved in the full development lifecycle from research to testing and documentation. Collaboration with ML researchers and systems engineers is key. | AgentServe | 7 |
| Engineering Manager, User & Content Intelligence Engineering Manager to lead a team building foundational ML systems for personalization on Apple's consumer platforms. The role involves managing ML engineers, defining technical strategy for distributed feature access and pipelines, and ensuring data quality and privacy compliance at petabyte scale. It bridges data engineering, ML systems, and privacy, focusing on the data layer that powers intelligent experiences. | DataServe | 7 |
| Quality Engineer - Machine Learning Quality Engineer for Machine Learning in Apple's Creative Music Apps team, focusing on testing ML models and DSP algorithms for audio features on macOS, iOS & iPadOS. Responsibilities include stress-testing for regressions, designing test strategies, developing automated tests, and collaborating with ML engineers on quality metrics. | Eval GatePost-train | 7 |
| Machine Learning Engineer, User & Content Intelligence Machine Learning Engineer focused on building foundational capabilities for personalization experiences across Apple's consumer products. The role involves engineering large-scale feature pipelines, architecting training data systems, and optimizing for privacy and scale, bridging edge devices and cloud backends. This is a senior-level role requiring expertise in distributed data processing and serving layers. | DataServe | 7 |
| AIML - Machine Learning Engineer - Computer Vision & Audio, MIND Machine Learning Engineer focused on the data and evaluation lifecycle for production models in computer vision and audio. Responsibilities include scaling data pipelines, ensuring data quality, performing failure analysis, implementing data augmentation, and designing evaluation metrics for models. The role bridges hardware, software, and modeling for efficient inference. | Eval GateData | 7 |
| Sr Software Engineer (Agentic AI), AI & Data Platforms This role focuses on building the backbone of an AI-powered developer platform that uses AI agents and autonomous workflows to support app development within Apple. The engineer will design and maintain backend services and orchestration systems for multi-agent AI workflows, integrate LLMs into developer tools, and work on cloud deployments and MLOps. | Agent | 7 |