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, 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 Researcher, Responsible AI Research role focused on responsible AI, fairness, and safety of Generative AI, including red teaming, developing mitigations, and evaluation frameworks for LLMs and foundation models within consumer products. | Post-trainAgent | 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 |
| Machine Learning Researcher - Apple Music - Recommender Systems Machine Learning Researcher for Apple Music focusing on recommender systems. The role involves researching, training, fine-tuning, and deploying AI/ML models for recommendation at massive scale, with a focus on connecting artists with music fans and enhancing user discovery. Requires a strong publication record and expertise in modern recommender methods. | ShipPost-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 |
| Staff Machine Learning Engineer, Search & Knowledge Platform Staff Machine Learning Engineer at Apple focused on Search and Knowledge Platform, developing next-generation Search and Question Answering systems using LLMs and RAG. Responsibilities include query understanding, retrieval, ranking, fine-tuning, and deploying models at scale, with a focus on production systems and online inference optimization. | ShipPost-train | 8 |
| Senior Computer Vision Machine Learning Engineer, Apple Wallet Senior Computer Vision ML Engineer at Apple, focusing on fraud and identity protection for Apple Wallet using facial recognition and adversarial object detection. The role involves applied research and production deployment of computer vision models. | Ship | 8 |
| Video Codec Machine Learning Engineer, Audio & Media Technologies The role focuses on developing next-generation video codecs by applying machine learning, deep learning, neural video compression, generative AI, and computer vision. It involves contributing algorithms to industry standards and collaborating with software and hardware teams. The role emphasizes ML-driven approaches to video coding and processing. | Post-train | 8 |
| Machine Learning Engineer, Video 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 across Apple platforms. The role involves applying ML, NLP, and generative AI to model user intent, optimize retrieval and ranking systems, and integrate advanced ML technologies into production features used by millions. Key responsibilities include designing and implementing retrieval/ranking systems, building/deploying LLM models, analyzing performance, and collaborating with cross-functional teams. | AgentServe | 8 |
| Senior iCloud Efficiency Engineer (GenAI & Agentic Systems) Senior Engineer to lead GenAI and agentic systems for improving efficiency in large-scale cloud infrastructure operations. Focuses on building practical AI systems for engineering workflows, capacity planning, anomaly detection, and operational safety, using LLMs, RAG, and automation frameworks. | AgentServe | 8 |
| Machine Learning Scientist - Personalization Science, Apple Media Products Machine Learning Scientist role focused on personalization for Apple's Media Products, involving research, development, and deployment of large-scale recommender systems for billions of users. The role requires expertise in deep learning, reinforcement learning, and generative AI applied to recommendations, with a strong emphasis on shipping production-quality code and contributing to scientific literature. | Ship | 8 |
| Sr. Machine Learning Research Engineer, Siri Speech Machine Learning Research Engineer for Siri Speech team, focusing on creating and productizing ML algorithms for Speech Recognition, Speech Synthesis, and Conversational AI on Apple devices and cloud infrastructure. Requires expertise in compiled languages, ML frameworks, and applied ML, with the ability to translate research into user-facing products. | Post-trainServe | 8 |
| Computer Vision Research Engineer - Apple Maps 3D Vision Team Research Engineer role focused on Computer Vision and Machine Learning for Apple Maps 3D Vision Team, developing novel methods for SLAM, 3D reconstruction, and localization using large, multi-modal datasets. | Data | 8 |
| Engineering Manager - GenAI, AI & Data Platforms (AiDP) Engineering Manager for GenAI, AI & Data Platforms at Apple, leading a team to build scalable GenAI platform and applications, including RAG and Agentic components, with a focus on distributed systems, inference, and enterprise adoption. | AgentServe | 8 |
| Machine Learning Tools Engineer, Global Siri Machine Learning Tools Engineer for Apple's Global Siri team, focusing on building and improving LLM-powered intelligent assistant systems. The role involves end-to-end ML product engineering, from data generation and model training to deployment and evaluation, with an emphasis on scalable solutions and software engineering best practices. | ShipPost-train | 8 |
| Machine Learning Engineer Machine Learning Engineer at Apple responsible for designing, building, and deploying scalable, production-grade AI/ML systems, with a focus on LLM-powered features and AI agent workflows. This role involves end-to-end solution development, from concept to deployment, including integration into existing systems and continuous improvement of ML infrastructure. | AgentServe | 8 |
| Staff Machine Learning Engineer Staff Machine Learning Engineer at Apple focused on building and scaling ML infrastructure and generative AI platforms. The role involves developing systems for ML data, embeddings, feature workflows, and enabling GenAI applications. Key responsibilities include designing scalable systems, improving experimentation and evaluation, optimizing inference and AI Ops, and prototyping/optimizing GenAI models for production. The role emphasizes end-to-end ML workflow experience, large-scale distributed systems, and modern generative techniques. | ServeData | 8 |
| ML Engineer - Automated Evaluation and Adversarial Design ML Engineer focused on building and scaling automated evaluation systems and designing adversarial/stress-testing methodologies for AI-powered features in productivity and creative applications. The role involves assessing AI quality, particularly for multi-turn agentic experiences, and influencing model development decisions through rigorous evaluation. | Eval GateAgent | 8 |
| Applied AI Scientist This Applied AI Scientist role at Apple focuses on building and deploying scalable ML and AI solutions to enhance product intelligence and automation, particularly for creative applications like video editing. The role involves end-to-end ML pipeline development, prototyping AI features, and collaborating with engineering and product teams to bring intelligent solutions to production. It requires strong experience in statistical modeling, machine learning algorithms, large-scale data systems, and deploying models into production, with a preference for generative AI, computer vision, and LLM experience. | Ship | 8 |
| Senior Applied Scientist - AI Evaluation & Quality Systems Senior Applied Scientist focused on building and scaling AI evaluation and quality systems. The role involves developing methodologies, tooling, and autonomous QA agents to ensure the trustworthiness and quality of AI/ML systems, with a strong emphasis on human-in-the-loop evaluation and anomaly detection. Requires a blend of research and engineering skills to prototype, validate, and ship solutions. | Eval GateAgent | 8 |
| Machine Learning Engineer, Siri Speech Machine Learning Engineer on the Siri Speech team at Apple, focusing on designing, developing, and implementing ML models for speech, NLP, and multimodal applications. This role involves fine-tuning deep learning systems for speaker recognition and multimodal understanding, integrating ML solutions into production at scale, and working with large datasets to build production-quality models. The position requires strong Python skills, experience with ML algorithms and deep learning frameworks like TensorFlow/PyTorch, and knowledge of speech/audio processing. | Post-trainServe | 8 |
| Machine Learning Engineer, Siri Attention & Invocation Machine Learning Engineer for Siri's Attention & Invocation team, focusing on on-device voice invocation experiences. Responsibilities include building and deploying models, end-to-end training and evaluation pipelines, and optimizing speech/audio processing for Apple devices. Requires strong ML/DL background, speech recognition experience, and software engineering skills. | Post-trainServe | 8 |
| WW Consulting Engineer - AI/ML This role is a customer-facing AI/ML consulting engineer focused on positioning Apple's platforms and solutions within enterprise, education, and government sectors. The engineer will provide deep domain expertise on AI/ML solutions (cloud, hybrid, on-device/edge), articulate technical value propositions, advise on scalability, guide integration of AI/ML capabilities, and translate market trends into actionable guidance. The role requires extensive knowledge of Apple's AI/ML stack, including Apple Silicon, Foundation Models, Core ML, and Private Cloud Compute, as well as experience with major cloud AI/ML platforms. | ServeAgent | 8 |
| AI/ML Software Engineer - SES Gen AI Solutions, IS&T AI/ML Engineer to design, develop, and deploy intelligent solutions for modern contact center platforms, focusing on scalable AI systems for chatbots, voice assistants, speech analytics, and automated customer support workflows. The role involves building end-to-end AI pipelines, including model development, deployment, and optimization, with deep expertise in LLMs, conversational AI, and real-time inference systems. | AgentServe | 8 |
| Machine Learning Software Engineer for Location and Spatial Awareness , Sensing & Connectivity Machine Learning Software Engineer at Apple focusing on spatial awareness and applied perception technologies. The role involves architecting and implementing production software systems for new ML technologies, particularly in computer vision, foundation models, and sensor-based perception. Key responsibilities include developing perception algorithms, optimizing ML training pipelines, fine-tuning vision transformers, and integrating ML with wireless and spatial sensors for iOS devices. | Post-trainServe | 8 |
| ML Engineer, Ai & Data Platforms ML Engineer to design, build, and deploy production AI and machine learning solutions for Apple's enterprise, focusing on Generative AI and Data Platforms. The role involves working across the full ML lifecycle, building automated ML pipelines, developing LLM-based solutions (RAG, agents), and integrating ML systems with the enterprise data platform. | AgentData | 8 |
| GPU Software Architecture Engineer, Graphics, Games, & ML This role focuses on architecting and building distributed ML infrastructure for large-scale inference, specifically for powering Apple Intelligence. It involves designing parallelization strategies, optimizing the stack from low-level access to high-level algorithms, and collaborating with hardware architects. The goal is to achieve maximum hardware utilization and minimize latency for real-time user experiences, serving billions of requests daily. | ServeAgent | 8 |
| Wireless Systems AI/ML Engineer, Wireless Technologies & Ecosystems This role focuses on building next-generation AI agents and tools for analyzing wireless connectivity and performance issues in Apple products. It involves developing advanced system evaluation and debugging capabilities using AIML tools, with an emphasis on improving user experience. The role requires expertise in ML frameworks, Gen AI techniques like RAG and Agent Orchestration, and Python scripting, with a strong understanding of wireless protocols. | AgentServe | 8 |
| Video Machine Learning Engineer, Audio & Media Technologies Video Machine Learning Engineer at Apple, focusing on designing, developing, and deploying ML solutions for video processing, understanding, and enhancement. The role involves researching, prototyping, training, evaluating, and optimizing models for on-device deployment across various Apple products. It bridges deep learning research with real-world product impact. | Post-trainServe | 8 |
| Senior Machine Learning Engineering Manager, Ads Quality This role is for a Senior Machine Learning Engineering Manager for Ads Quality at Apple. The primary focus is on leading a team to build and deploy ML models that ensure the quality and integrity of the ad network, with a specific emphasis on using LLMs for relevance, safety, and trustworthiness. The role involves developing and applying advanced ML techniques in a large-scale production environment, working across product, policy, and engineering teams, and analyzing large-scale experiments. | ShipPost-train | 8 |
