Currently tracking 171 active AI roles, down 37% versus the prior 4 weeks. Primary focus: Agent · Engineering. Salary range $120k–$487k (avg $235k).
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.
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 |
|---|---|---|
| Software Engineer - Intelligent Engineering Workflows Software Engineer to design and build intelligent tooling, automation, and AI-powered workflows using AI agents to improve engineering productivity and software quality across Apple's media technology stack. This role involves prototyping and productizing systems that leverage agentic coding workflows, AI-driven code analysis, and automation pipelines to streamline development processes, accelerate issue resolution, and enhance code quality at scale. | Agent | 7 |
| Sr./Staff ML Infrastructure Engineer, Compute (TPU Scheduling) - Foundation Model This role focuses on designing and developing scheduling and orchestration systems for large-scale TPU workloads in multi-region clusters, supporting foundation model training and inference. It involves distributed systems, cluster management, and performance optimization. | Serve |
| 7 |
| Computational Photography/Computer Vision Machine Learning Engineer, Camera & Photos Develop and train deep learning models for image restoration and fusion applications to improve Apple's camera imaging pipeline, contributing to consumer products. | Ship | 7 |
| Software Engineering Manager, Wallet Identity Engineering Manager for Wallet Identity Services at Apple, focusing on leading a team that builds and operates ML-powered services for liveness detection, face matching, and image quality. The role involves full lifecycle ownership of these services, from architecture and development to deployment and monitoring, with a strong emphasis on MLOps and scaling ML models in production. | ServePost-train | 7 |
| Sr Engineering Program Manager, AI/ML Technical Program Manager to help shape the future of scalable machine learning infrastructure. Lead planning, execution, and cross-functional coordination across engineering teams to deliver robust, high-performance ML systems that operate across Apple’s cloud and distributed environments. Define and run processes that ensure the timely delivery of GPU, compute, and data infrastructure components that support large-scale ML workloads. | ServeData | 7 |
| Subject Matter Expert - Automation & AI/ML This role focuses on developing and implementing next-generation automated processes for cosmetic and protective finishes (PVD coatings, Ink Printing) in high-volume manufacturing. It involves both physical automation (robotics, PLCs) and digital automation, including machine vision and deploying ML/AI models for predictive maintenance, defect detection, and process optimization. The role requires integrating automation parameters with materials chemistry and collaborating with cross-functional teams. | AgentServe | 7 |
| Staff AI Software Engineer, Siri Core Modeling Staff AI Software Engineer for Siri Core Modeling at Apple, focusing on the on-device software platform for Apple Intelligence. The role involves leading design and development of features, implementing performant code, identifying architectural changes, optimizing performance, and developing software that interfaces with LLMs and on-device intelligence to enhance Siri capabilities. The position also emphasizes leveraging LLMs and AI assistants for engineering productivity. | Agent | 7 |
| Location Estimation Scientist, Sensing & Connectivity This role focuses on building and maintaining production-grade software systems and ML models for location intelligence using sensor data. It involves the full ML lifecycle from problem formulation to production deployment, with a strong emphasis on signal processing, data infrastructure, and scaling ML to hundreds of millions of devices. | Serve | 7 |
| Engineering Program Manager, Search Quality and Infrastructure, Apple Services Engineering Engineering Program Manager to drive the execution of large-scale, machine learning-powered search products and infrastructure at Apple, focusing on improving user experience and quality for over a billion customers. | Ship | 7 |
| Engineering Project Manager - AI Features Internationalization, L&RE Engineering Project Manager responsible for the internationalization and global launch of AI-driven products, including Apple Intelligence. This role involves leading technical integration of generative AI and ML features across multiple languages and countries, managing international data generation, and driving model evaluation strategy for audio, vision, and language models. | Post-trainData | 7 |
| Tech Lead Machine Learning Engineer - Finance Digital Transformation Tech Lead Machine Learning Engineer for Finance Digital Transformation at Apple. The role focuses on building data foundations, services, and platforms for insights and automated decisions within the Finance organization, specifically for product cost. Responsibilities include technical leadership, operationalizing AI solutions from prototype to production, and instilling ML engineering practices. Requires experience in ML algorithms, generative AI, agentic solutions, MLOps/LLMOps, data pipelines, and Python. | AgentServe | 7 |
| 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 |
| 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 |
| 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 |
| 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 |
| 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 |
| 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 |
| 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 |
| 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 |
| 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 |
| 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 |
| 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 |
| Senior Software Engineer: Agentic Systems, Instructional Products Senior Software Engineer to design and build intelligent tooling and automation using AI-driven agents to improve engineering productivity and content operations. The role involves prototyping and productionizing systems that leverage agentic coding workflows and AI-driven content processing to streamline development and publishing processes. | Agent | 7 |
| Senior ML Software Engineer, Watch Software Senior ML Software Engineer for Apple Watch, focusing on developing and deploying ML models on-device using multimodal sensor data. The role involves the full ML lifecycle from research to productization, with an emphasis on power-efficient, on-device inference for consumer features. | ServePost-train | 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 Machine Learning Engineer - Ads Auction Senior Machine Learning Engineer at Apple focused on building and optimizing the core auction system for their advertising platform. The role involves applying machine learning and auction theory to drive optimal outcomes for advertisers and users, working with large-scale systems and production code. | Ship | 7 |
| Senior Machine Learning Engineer - Ads Bidding & Pacing Senior Machine Learning Engineer at Apple focused on Ads Bidding & Pacing. The role involves designing and building scalable ML solutions for ad optimization, budget, and bid strategies to improve campaign performance and user experience. Requires experience in ML, quantitative optimization, production code development, and large-scale experimentation, ideally within the ads, recommendations, or search relevance domains. | Ship | 7 |
| Senior Machine Learning Engineer – Ads Predictions Senior Machine Learning Engineer at Apple Ads focusing on building and optimizing core ML models for ad predictions, user interaction, click-through rate, and conversion rate. The role involves deep learning, information retrieval, large-scale modeling, and exploring LLMs and Reinforcement Learning for ad prediction systems across Apple's App Store and News platforms. | ShipServe | 7 |
| Staff Machine Learning Engineer : Platform Intelligence - Apple Maps Staff Machine Learning Engineer for Apple Maps focused on designing, developing, and deploying on-device ML models. This role requires optimizing for performance on Apple platforms, collaborating cross-functionally, and mentoring junior engineers. Experience with ML frameworks, systems programming, and shipping production ML models on mobile/embedded devices is critical. | ServePost-train | 7 |
| Staff Data Science Engineer, Siri Runtime Systems and Interaction Staff Data Science Engineer for Siri's Attention and Invocation team, focusing on making Siri and Apple products more intelligent. The role involves leading ML solution development, establishing best practices for model validation and monitoring, driving technical decisions for ML/AI initiatives, and collaborating with stakeholders to define requirements and shape the data science roadmap. | Ship | 7 |
| Machine Learning Systems Engineer, Siri Runtime Systems and Interaction Machine Learning Systems Engineer for Siri at Apple, focusing on integrating, optimizing, and deploying ML models into production software pipelines for resource-constrained platforms. The role involves building infrastructure for ML evaluation and analysis, collaborating with ML engineers, and ensuring performance and reliability of ML workloads within the Siri ecosystem. | ServeEval Gate | 7 |
| Staff Machine Learning Engineer – Ads Platform Staff Machine Learning Engineer for Apple Ads Platform, focusing on building and deploying ML systems and data pipelines to enhance advertiser trust and invalid traffic protections. The role involves defining an innovation roadmap, implementing robust CI/CD, feature stores, and streaming infrastructure, running A/B experiments, and optimizing performance for product quality, user experience, latency, and cost. | Ship | 7 |
| Computer Vision Software Engineer, Camera & Photos Develop and extend software features for iPhone camera, focusing on computer vision, image processing, and machine learning to deliver high-quality photos and videos. This role involves prototyping algorithms, working cross-functionally, and implementing solutions for new camera capabilities across Apple devices. | Ship | 7 |
| Manager, Machine Learning Engineering Manager for a Machine Learning Engineering team focused on manufacturing applications at Apple. The role involves leading a team of ML and MLOps engineers to build, deploy, and scale AI-driven systems for the product lifecycle, from prototype to announcement. Requires technical expertise in AI, leadership skills, and experience with MLOps, Computer Vision, and scaling ML systems. | Serve | 7 |
| Applied ML Science Manager The Applied ML Science Manager will lead a team focused on Causal Inference and AIML solutions for Apple's services, impacting business decisions and marketing optimization. The role involves developing and deploying cutting-edge solutions, defining technical vision, and fostering a collaborative team culture. Responsibilities include leading scientists and engineers, overseeing technical strategy, managing projects, and collaborating with cross-functional teams. Requires a Master's degree, leadership experience, and expertise in Causal Inference techniques, ML, and programming languages. | Ship | 7 |
| AIML - Software Engineer - AI, Evaluation Software Engineer role focused on building tools and systems for the automatic evaluation of Apple's AI products, specifically using LLM-as-judge and related technologies to improve the quality and efficiency of these evaluations. The role involves designing and developing frameworks, pipelines, and tools for AI model development, deployment, and measurement, directly impacting product launch decisions. | Eval GateAgent | 7 |
| Software Engineer, Machine Learning & AI Software Engineer role focused on developing and delivering AI/ML solutions for Apple's hardware product line, including agentic systems and RAG architectures, with responsibilities spanning training, evaluation, and inference pipelines. | AgentServe | 7 |
| Industrial Machine Learning Engineer This role focuses on applying machine learning and computer vision to industrial problems in manufacturing, specifically for inspection equipment. The engineer will develop and deploy ML models to judge millions of units daily, identify patterns and anomalies in data, and build toolkits for applying ML and statistical tools. Responsibilities include data analysis, software development in Python/Java/C++, and working with inspection systems. The role requires strong ML/CV experience in industrial settings, proficiency in Python and ML algorithms, and experience with image processing. It involves developing solutions from inception to production, with a focus on shipping AI-powered products for quality control in manufacturing. | ShipServe | 7 |
