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 |
|---|---|---|
| Engineering Manager, Maps Search Intelligence Engineering Manager for Apple Maps Search Intelligence team, responsible for leading the design, development, and production deployment of core search algorithms, large-scale ML models, and generative AI systems. The role involves defining the technical roadmap, driving execution across the ML lifecycle, and partnering with product and design teams to shape the future of Maps Search and integrate with Apple Intelligence. | AgentServe | 9 |
| Machine Learning Engineer - Large Language Models & Generative AI Inference Machine Learning Engineer focused on the inference platform for Large Language Models and Generative AI, working with foundation models and client teams to enhance user experiences across Apple's operating systems. The role involves translating research into high-performing systems and optimizing the model serving stack. |
| Serve |
| 9 |
| Machine Learning Engineer Machine Learning Engineer focused on Evaluation & Insights for the Human-Centered AI team at Apple Media Services. The role involves evaluating and optimizing Foundation Models and generative AI systems, architecting evaluation frameworks, designing MLOps pipelines, and translating failure modes into guardrails and training signals. This position bridges human perception and algorithmic performance, working cross-functionally to ensure AI experiences are reliable, safe, and aligned with human expectations. | Eval GatePost-train | 9 |
| Machine Learning Engineer, Proactive Machine Learning Engineer focused on developing, fine-tuning, and evaluating Large Language Models for various NLP tasks like summarization, question answering, and search relevance, with a strong emphasis on transferring cutting-edge generative AI research into production-ready technologies for Apple's AI-powered products. | Post-trainAgent | 9 |
| Machine Learning Engineer, Apple Services Engineering Machine Learning Engineer at Apple Services GenAI & ML Frameworks team, focusing on bridging foundation model capabilities with real-world production systems. The role involves LLM continual pretraining, posttraining, agentic reinforcement learning, and agentic system optimization to improve LLM domain knowledge, tool use, reasoning, and system integration for user-facing features at scale. | Post-trainAgent | 9 |
| Machine Learning Engineer Machine Learning Engineer to design and build GenAI-powered features and workflows leveraging LLMs and modern AI techniques for supply chain optimization. Responsibilities include end-to-end GenAI capability development, prompt and tool design, agent orchestration, retrieval strategies, model selection, system evaluation, Text-to-SQL development, and establishing guardrails. Will also focus on inference and serving in production. | AgentServe | 9 |
| Machine Learning Engineer, Apple Intelligence ML Engineer focused on building and optimizing generative models for international languages, covering the full pipeline from data preprocessing to deployment. | Post-trainServe | 9 |
| Machine Learning Architect - Conversational Speech Machine Learning Architect for Conversational Speech at Apple, responsible for defining modeling strategy and technical direction for speech recognition, synthesis, dialog systems, multimodal foundation models, and speech-to-speech technologies. The role involves hands-on technical leadership, translating research into production-quality systems at scale, and ensuring architectural decisions align with on-device constraints, latency, and scalability. | Post-trainAgent | 9 |
| AIML - Sr Machine Learning Engineer, Data and ML Innovation Senior Machine Learning Engineer at Apple focused on innovating and applying state-of-the-art research in foundation models, particularly for audio data. The role involves the full ML pipeline from pre-training on large-scale unlabeled audio corpora to post-training evaluation and fine-tuning. Responsibilities include designing multi-modal data generation frameworks, building model evaluation pipelines, analyzing multi-modal data, and contributing to products with multi-modal perception data, especially audio and sensor fusion. The role also emphasizes representation learning, pre-training/fine-tuning for speech tasks, data selection techniques, and modeling data distributions. Collaboration with researchers and engineers is key, with opportunities for publishing groundbreaking research. | PretrainPost-train | 9 |
| Applied AI Engineer Applied AI Engineer at Apple Sales, focused on crafting and operating AI solutions using LLMs and agentic workflows for business problems. Responsibilities include designing agentic AI systems, translating research into production, building scalable pipelines, and leading technical decisions on infrastructure and safety mechanisms. Requires PhD or MS with significant experience in applied AI/ML, Python proficiency, and hands-on experience with LLMs, embeddings, vector databases, and agentic workflows. | AgentServe | 9 |
| Senior Machine Learning Manager, Search & Knowledge Platform Lead the E2E R&D and engineering for Generative AI models focused on summarization capabilities, including on-device and server-side LLMs, groundedness, and safety models. Develop inference frameworks and integrate with Apple's LLM infrastructure to deliver user experiences across various Apple products. | Post-trainServe | 9 |
| AIML - Applied Research Engineer, Machine Translation Applied Research Engineer focused on Machine Translation, leveraging LLMs and reinforcement learning to improve translation quality for Apple's products. The role involves end-to-end model development, from data generation and training to evaluation and production rollout, with a focus on scalability and quality. | Post-trainServe | 9 |
| Machine Learning Engineer Machine Learning Engineer focused on Evaluation & Insights for the Human-Centered AI team. This role involves architecting evaluation frameworks, designing MLOps pipelines for model assessment, and translating qualitative failure modes into programmatic guardrails and training signals for Foundation Models and generative AI systems. The role also involves collaborating with various teams to ensure AI experiences are reliable, safe, and aligned with human expectations. | Eval GatePost-train | 9 |
| Senior Computer Vision and Machine Learning Engineer, Creator Studio Senior Engineer to work on Generative AI for creative editing tools, focusing on computational photography and multi-modal image editing. Responsibilities include incubating ML algorithms, owning the model lifecycle (training to inference), designing data pipelines, and communicating research. Requires MS/PhD with 5+ years experience, deep ML knowledge (multimodal LLMs, MoE, PEFT, RLHF), and experience delivering customer-facing CV/GenAI products. | Post-trainServe | 9 |
| Machine Learning Systems Engineer, Siri Agent Modeling Machine Learning Systems Engineer for Siri, focusing on optimizing model training and inference for generative AI technologies on Apple Silicon. This role involves working across the ML stack, from training to deployment, to deliver production-level code for models impacting millions of users. | ServePost-train | 9 |
| Evaluation & Insights Machine Learning Engineer This role focuses on evaluating and improving AI systems by analyzing AI outputs, developing evaluation frameworks, and translating findings into actionable improvements. It involves assessing model behavior, identifying edge cases, and ensuring AI systems are reliable, safe, and aligned with human expectations. The role also involves building MLOps and automation for evaluation pipelines and collaborating with various teams to refine model performance. | Eval GatePost-train | 9 |
| Senior Engineering Manager, Applied AI & Agentic Experiences Senior Engineering Manager to lead Applied AI experiences for Channel Sales, focusing on intelligent workflows, conversational experiences, and agentic AI capabilities for the end-to-end Commerce Journey. This role involves leading a team, driving product engineering strategy, and shipping ML-powered products and features, ideally involving LLMs and AI agents. | AgentServe | 9 |
| Senior Computer Vision and Machine Learning Engineer, Creativity Apps Senior Computer Vision and Machine Learning Engineer at Apple focused on Generative AI for creative editing tools. The role involves incubating, training, evaluating, and deploying ML models, particularly diffusion models, transformers, and GANs, with a focus on computational photography and multi-modal image editing. The engineer will also work on efficient inference and collaborate with cross-functional teams to bring these technologies to Apple products. | Post-trainServe | 9 |
| Sr. Applied ML Engineer, Apple Services Localization Engineering This role focuses on designing, building, and shipping machine translation and LLM-based systems for Apple Services Localization. It involves taking models from prototype to production, owning serving, inference, and data pipelines, integrating ML models into existing systems, driving applied research (LLM fine-tuning, model compression, agentic workflows, RAG), and building evaluation infrastructure. The role requires strong software engineering skills and experience with deep learning toolkits, large models, and distributed production systems. | ShipServe | 8 |
| Machine Learning Engineer Machine Learning Engineer at Apple working on Siri, Spotlight, and Safari search features. The role involves large-scale machine learning and deep learning for query understanding and ranking, using techniques like word embeddings, online learning, and NLP. It also includes building infrastructure for processing web-scale data, deploying metrics and evaluations, and presenting results. Experience with RAG is preferred. | ShipAgent | 8 |
| Sr. ML Production Model Automation Engineer, Siri Speech This role focuses on automating the production model lifecycle for Siri's speech and audio features, which are powered by multimodal, on-device AI. The engineer will build and operate agent-based automation pipelines for ML model training, iteration, staging, rollout, and deprecation, including SFT, LoRA, and RL phases. The work involves developing multi-agent workflows for evaluation, triage, and root cause analysis, and owning the launch tooling for training jobs. | Post-trainServe | 8 |
| Machine Learning Manager - AI, Search & Knowledge Platforms Machine Learning Manager to lead a team building AI, Search, and Knowledge Platforms for Apple products like Siri and Apple Intelligence. The role focuses on integrating LLMs with server-side architectures to deliver scalable, reliable, and user-centric AI services and agentic systems. | AgentServe | 8 |
| Language Engineer (Arabic), Global Siri Language Engineer for Siri in Arabic, focusing on end-to-end user experiences by applying ML and NLP techniques. Responsibilities include data-driven analysis, designing and implementing innovations for global markets, and developing/training LLMs for internationalization challenges. Requires native Arabic fluency and strong software engineering skills. | Post-trainServe | 8 |
| Senior AI Engineer Senior AI Engineer role focused on building and operating LLM-powered applications and agentic AI systems for Apple Sales. Responsibilities include designing, prototyping, and productionizing intelligent agents, retrieval pipelines, and embedded AI features, integrating structured and unstructured data, and leading technical decisions on infrastructure and safety mechanisms. Requires strong Python, LLM, RAG, and agent orchestration framework experience. | Agent | 8 |
| Machine Learning & AI Engineer This role focuses on developing and implementing AI solutions, particularly in computer vision and NLP, to improve failure analysis and lab operations. It involves leading research, design, and development of advanced AI models, building software pipelines for training and deployment, and integrating AI into real-world applications. | Post-trainAgent | 8 |
| Machine Learning Engineer, Apple Intelligence Data Platform - Proactive Machine Learning Engineer focused on building and deploying scalable agent systems for Apple's on-device and cloud-based intelligence features, including Siri Suggestions and proactive intelligence. The role involves personalization, context-awareness, and integration with LLMs, vector databases, and knowledge graphs to enhance user experiences across Apple devices. | AgentServe | 8 |
| Machine Learning Engineer, ASE Search Team Machine Learning Engineer on the Video Search team at Apple, focusing on building and deploying large-scale ML systems for search and discovery in the Apple TV App, Siri, and Spotlight. The role involves applying ML, NLP, and generative AI to model user intent, optimize retrieval and ranking, and enhance search relevance and personalization using cutting-edge technologies and adhering to strict privacy standards. | AgentServe | 8 |
| Machine Learning Engineer, ML/GenAI Evaluation Machine Learning Engineer focused on evaluating ML and GenAI models for Wallet, Payments, and Commerce features. This role defines evaluation criteria, metrics frameworks, and quality standards, designs adversarial test strategies, and owns the model quality sign-off process to ensure models meet high standards for accuracy, robustness, fairness, and reliability before shipping to hundreds of millions of users. Responsibilities include building test sets, developing robustness testing methodologies, owning fairness evaluation end-to-end, evaluating generative model outputs, and synthesizing results for product decisions. | Eval Gate | 8 |
| Staff Machine Learning Engineer – Ads Signals Intelligence & Information Retrieval Staff Machine Learning Engineer for Apple Ads, focusing on building ML-driven signal platforms for retrieval, prediction, and relevance. The role involves developing content understanding systems and large-scale infrastructure for near real-time signal updates, using LLM fine-tuning, knowledge graphs, semantic search, and multimodal learning. The primary output is an agentic system for ad delivery, with a secondary focus on the inference infrastructure supporting it. | AgentServe | 8 |
| Senior Software Engineer - Generative AI & ML, Customer Systems Senior Software Engineer role focused on Generative AI and ML within Apple's Customer Systems IS&T organization. The role involves contributing to model development, fine-tuning, designing retrieval strategies for grounding models, prototyping multi-agent systems, and ensuring scalable deployment. The team builds multi-turn, conversational, agentic applications and frameworks for customer support, enhancing a multi-modal, multi-agent platform with a focus on research to improve latency, cost, and customer experience. | AgentPost-train | 8 |
| AIML - ML Engineer, Responsible AI ML Engineer focused on Responsible AI, developing models, tools, and metrics for assessing and evaluating the safety, robustness, and uncertainty of generative models (vision and language). This includes interpreting model failures, building human annotation and red teaming pipelines, and prototyping/implementing/evaluating new ML models for red teaming LLMs. | Eval GatePost-train | 8 |
| Data Scientist, EMEIA Sales This role focuses on developing and deploying AI-powered applications, specifically agentic systems, for sales use cases. The Data Scientist will research, test, and implement these solutions, working with various stakeholders to drive AI adoption and educate non-technical teams. The role involves hands-on work with LLMs, agent frameworks, and prompt engineering, with a good understanding of RAG and vector databases. | Agent | 8 |
| AI / Data Engineer The AI/Data Engineer will focus on building AI-powered applications, scalable backend systems, and Generative AI solutions for supply chain and logistics. This role involves modern AI engineering, prompt engineering, and intelligent application development, including designing agentic AI capabilities, multi-agent workflows, and orchestration patterns. The engineer will also build and optimize backend AI and data services, develop prompts and evaluation methodologies, and support the deployment and operationalization of AI solutions. | AgentData | 8 |
| AI/ML Engineer (GenAI), G&A Solutions Engineering (GSE) AI/ML Engineer role focused on building a next-generation payments platform using Generative AI, Agentic AI, and LLMs. The role involves modernizing complex product architectures for reconciliation, invoicing, and payments, and transforming transactional data processing. | AgentPost-train | 8 |
| SWE - Machine Learning Engineer, Photos Machine Learning Engineer for Apple's Photos app, focusing on developing and deploying privacy-preserving ML, deep learning, and generative AI algorithms for Apple Intelligence features. The role involves taking ML algorithms from prototype to production quality, with a focus on LLMs and inference optimization. | ShipPost-train | 8 |
| Computer Vision and Machine Learning Engineer, Creativity Apps This role focuses on building and delivering state-of-the-art machine learning models for creative editing tools, specifically in computer vision and generative AI. The engineer will be responsible for the end-to-end lifecycle of ML-enabled features, from data collection and model design to training, evaluation, and deployment within applications. | Ship | 8 |
| Machine Learning Engineer — Generative Models, Productivity Apps Machine Learning Engineer focused on generative models for productivity apps, involving design, training, evaluation, and end-to-end feature delivery from research prototype to production. Requires experience with generative models like diffusion and transformers, and programming in PyTorch or JAX. | Post-trainServe | 8 |
| 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 |
| Principal AI Architect, App Store Data Principal AI Architect role focused on designing and shipping AI systems, including agentic workflows and LLM-powered data products, for the App Store. The role involves translating business problems into AI initiatives, guiding AI strategy, designing production-grade AI systems, and ensuring adherence to security and compliance policies. Requires extensive experience with LLMs, agentic workflows, and building/deploying AI/ML solutions in production. | AgentServe | 8 |
| Senior Software Engineer, Machine Learning & AI Senior Software Engineer on the Product Integrity AI/ML team at Apple, focusing on developing and deploying AI/ML solutions for hardware product design, manufacturing, and testing. The role involves building scalable infrastructure for ML workflows, including agentic systems, and applying techniques like LLMs, custom model training, and RAG to hardware challenges. The position requires strong software engineering skills, leadership, and mentorship. | AgentServe | 8 |
| AI Engineering Manager - GenAI Platform , Infra & AIOps AI Engineering Manager to lead planning and execution for next generation AIML Platforms, Infrastructure and AIOps for Channel Sales at scale. Drive vision, roadmap, and execution of innovative AI solutions leveraging generative models. Collaborate with cross-functional teams to develop breakthrough AI products. | ShipServe | 8 |
| Silicon Automation Engineer - Robotics and AIML Seeking an automation engineer with expertise in Silicon Validation, robotics control, AIML, and software development to build an intelligent automation system for silicon validation. The role involves integrating software and hardware, controlling robotics with computer vision and ML, and implementing AI/ML models for detection, collision avoidance, and control. | Agent | 8 |
| Senior Machine Learning Engineer, Agentic Workflows - Software Delivery Senior Machine Learning Engineer focused on building agentic workflows to improve Apple's software delivery and developer productivity. This role involves designing and implementing ML pipelines, developing intelligent systems for code analysis and search, and leading the design of generative AI solutions. | AgentServe | 8 |
| Director of Algorithms, Ads Engineering Director of Algorithms for Apple Ads, leading applied scientists and ML engineers to build and scale intelligence for ads delivery. Focuses on retrieval, ranking, auction, and budget optimization systems at massive scale, balancing research innovation with operational excellence and privacy constraints. This role involves defining strategy, roadmap, and execution for ML systems that optimize advertiser outcomes and user relevance. | ShipServe | 8 |
| AI Engineer - Wireless Systems Analysis , Wireless Technologies & Ecosystems AI Engineer role focused on developing and deploying generative AI/LLM solutions for wireless systems performance analysis. Responsibilities include architecting RAG pipelines, fine-tuning LLMs, building backend services, and establishing evaluation frameworks, with a focus on wireless log analysis and telecom-specific use cases. | AgentServe | 8 |
| Sr. Machine Learning Engineer, Siri Speech This role focuses on advancing Siri's conversational AI capabilities by designing, training, and evaluating machine learning models for production use cases. It involves building and maintaining scalable ML pipelines, optimizing models for performance, and contributing to ML infrastructure. The role requires experience across the full ML lifecycle, from data processing to deployment, with a focus on speech synthesis and recognition, natural language understanding, and dialog generation. | Post-trainServe | 8 |
| Applied Machine Learning Engineer - Developer Publications Applied Machine Learning Engineer focused on building and maintaining LLM evaluation pipelines for developer tools at Apple. The role emphasizes MLOps/LLMOps, assessing model quality, tracking regressions, and supporting continuous improvement cycles, requiring strong engineering fundamentals and LLM evaluation experience. | Eval GatePost-train | 8 |
| Software Engineer - Generative AI & ML, Customer Systems Software Engineer role focused on building multi-turn, conversational, agentic applications and frameworks for customer support, enhancing a multi-modal, multi-agent platform with a focus on research to improve latency, cost, and customer experience. Involves model development, fine-tuning, retrieval strategies, and multi-agent system prototyping. | AgentData | 8 |
| Staff Applied Scientist, AI Quality & Meta Evaluation Staff Applied Scientist focused on AI Quality & Meta Evaluation, responsible for designing and building the Data Quality Validation framework for LLM Judges. This role involves developing statistical and ML approaches to ensure the trustworthiness of evaluation signals, auditing LLM outputs, and establishing standards for data quality. | Eval GatePost-train | 8 |
| Applied AI Engineer - iCloud Data This role focuses on building and scaling AI-native capabilities within Apple's iCloud data platform. The engineer will design, build, and own end-to-end AI systems, including agents, retrieval mechanisms, evaluation, guardrails, and observability. Key responsibilities involve optimizing AI systems for cost and performance, exploring state-of-the-art AI techniques, and educating the broader organization on AI patterns. The role requires experience in taking LLM or agentic systems from prototype to production, proficiency in modern AI frameworks, and a strong understanding of ML/DL principles. | AgentServe | 8 |