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, SIML Machine learning research engineer with experience building modern generative models based on diffusion and auto-regressive technologies. Focus on training and adapting large scale image/video/audio/multimodal foundation models, staying at the forefront of AI research, and pioneering proprietary ideas for Apple's ecosystem. Experience with training and fine-tuning modern image/video generation models is required. | Post-trainPretrain | 9 |
| Principal Research Scientist, Siri Innovation Studio Principal Research Scientist for Siri Innovation Studio at Apple, focusing on incubating and deploying next-generation AI features for Apple Intelligence. The role involves leading end-to-end ML research and development, from ideation to shipping at scale, with a strong emphasis on applied ML, agentic systems, and user-centered design for a wide range of Apple products. Requires a strong publication record and experience with ML model lifecycles. |
| ShipAgent |
| 9 |
| 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, 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 |
| Senior Applied Researcher Senior Applied Researcher with expertise in Generative AI, LLM architectures, and advanced NLP systems. The role involves architecting, designing, and deploying LLM-powered systems for personalization, automation, and customer understanding across Apple Services. Responsibilities include research in representation learning, semantic modeling, NLU, RAG, fine-tuning, evaluation, safety alignment, and exploring methods like parameter-efficient adaptation, multi-agent orchestration, and RLHF. The role also involves building prototypes and production-grade solutions, contributing to patents/publications, and mentoring other researchers. Requires a Ph.D. or equivalent experience, expert knowledge of deep learning/NLP/transformers, LLM development, Python, and ML frameworks, with experience deploying models in production. | AgentPost-train | 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 |
| 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 |
| AIML - Machine Learning Engineer in Foundation Models, Responsible AI and Safety The role focuses on applied research in responsible AI and safety for foundation models, including training, evaluation, alignment, and mitigations for deployment in Apple products. It involves collaboration with researchers and engineers to develop and deliver AI technologies that uphold Apple's values and privacy standards. | Post-trainAgent | 9 |
| Machine Learning Engineer — Camera & Photos, Creative Foundations Machine Learning Engineer and Researcher to join the Creative Foundations team within Camera & Photos. This role involves inventing novel ML models at the intersection of research and product features, focusing on image understanding for consumer-facing applications. Responsibilities include designing architectures, training strategies, and intelligent systems, translating research into shippable features, and leveraging interpretability techniques. Requires MS/PhD, experience in ML/computer vision, proficiency in ML frameworks, and understanding of modern ML architectures. Preferred qualifications include a track record of creative problem-solving, published research, and specific computer vision experience. | Post-trainServe | 9 |
| Research Scientist, Applied Machine Learning Security (Agent Systems), SEAR Staff-level ML Security Research Scientist focused on applied research for production agentic ML systems, particularly tool-using models. The role involves leading research to identify and mitigate security vulnerabilities in these systems, designing realistic adversarial evaluations, and driving defenses into shipping products. The emphasis is on production impact and risk reduction, bridging research, platform engineering, and product security. | Agent | 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 |
| AIML - Machine Learning Researcher, MLR Apple is seeking a Machine Learning Researcher to conduct foundational research in LLMs and generative models, focusing on long-term, curiosity-driven projects. The role involves defining and executing research plans, implementing experiments, and publishing results in top-tier scientific venues. Collaboration with ML engineers and researchers across Apple is expected, with opportunities for technical mentorship. | PretrainPost-train | 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 |
| 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 |
| 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 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 |
| 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 |
| 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 |
| 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 |
| 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 |
| 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 |
| 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 |
| 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 |
| 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 |
| 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 |
| 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 Predictions This role is for a Senior Machine Learning Engineering Manager at Apple, focusing on Ads Predictions. The manager will lead a team responsible for building and scaling complex ML models for response prediction (CTR, conversion rate) under latency constraints. Key responsibilities include driving the development and deployment of state-of-the-art models, owning the full ML lifecycle from data to production serving, and championing privacy-preserving ML approaches. The role requires strong leadership, cross-functional collaboration, and hands-on experience with large-scale ML systems, including neural networks and LLM-based systems. | ServePost-train | 8 |
| ML Applied Scientist, Apple Services Engineering AI/ML ML Applied Scientist role focused on designing, developing, and deploying AI/ML solutions for Apple's services, including LLMs and Agentic AI, to enhance user content discovery. The role involves research, prototyping, production deployment, A/B testing, and collaboration with cross-functional teams. | ShipPost-train | 8 |
| AIML - Sr Machine Learning Engineer, Data and ML Innovation Machine Learning Engineer at Apple focused on innovating and applying state-of-the-art ML research to complex data problems, specifically for Apple Intelligence. The role involves designing and developing a data generation and curation framework for foundation models, building evaluation pipelines, and exploring new methods for synthetic data creation across vision, text, and audio. The position also emphasizes collaboration with multidisciplinary teams and potentially publishing research. | DataPost-train | 8 |
| Senior Machine Learning Engineer (Generative AI) Senior Machine Learning Engineer focused on Generative AI, responsible for converting high-level goals into concrete requirements, implementing, evaluating, and shipping AI/ML technologies for data quality or user-facing features. Requires experience in building large-scale ML systems, generative AI models, and working with large datasets, with a strong emphasis on shipping production-ready solutions. | ShipPost-train | 8 |
| Machine Learning Engineer - LLM Machine Learning Engineer to build a GenAI system for Apple Audio products, focusing on LLM/LMM development, agents, and RAG applications. Requires experience in ML algorithms, software engineering, and data mining with LLMs/LMMs. | AgentPost-train | 8 |
| AIML - Sr Machine Learning Engineer, Responsible AI This role focuses on developing, carrying-out, interpreting, and communicating pre- and post-ship evaluations of the safety of Apple Intelligence features, leveraging both human and model-based auto-grading. It also involves researching and developing auto-grading methodology & infrastructure. The role requires creating safety evaluations that uphold Responsible AI values through data sampling, curation, annotation, auto-grading, and analysis. It draws on applied data science, scientific investigation, cross-functional communication, and metrics reporting. | Eval GatePost-train | 8 |
