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 |
|---|---|---|
| AIML - Machine Learning Researcher, MLR This role is for a mid-level to senior Machine Learning Researcher focused on ambitious, curiosity-driven, long-term foundational research projects. The researcher will push the boundaries of ML, publish in top-tier venues, and collaborate with ML engineers and researchers to impact future Apple products. Requires demonstrated expertise, a publication record, and hands-on experience with deep learning toolkits like PyTorch. | Pretrain | 10 |
| AIML - Machine Learning Researcher, MLR Seeking junior and mid-level researchers for foundational ML research impacting Apple products. Role involves self-directed and collaborative research, publishing results, and providing technical mentorship. Requires expertise in ML research topics like RL, LLM training/adaptation, reasoning, diffusion models, audio, and multimodal models, with a strong publication record and deep learning toolkit experience. |
| Pretrain |
| 10 |
| AIML - Machine Learning Researcher, MLR This role is for a mid-level to senior Machine Learning Researcher focused on foundational, long-term research projects that will impact future Apple products. The researcher will push the boundaries of ML research, publish in top-tier venues, and collaborate with other researchers and engineers. A PhD or equivalent experience and a strong publication record are required. | Pretrain | 10 |
| 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 - 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, 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 |
| Sr. Machine Learning Research Engineer, Siri Speech This role focuses on advancing Siri's conversational AI capabilities by developing and deploying novel deep learning technologies for efficient speech and multi-modal modeling. The primary goal is to improve Siri's intelligence, naturalness, and usefulness, with a strong emphasis on efficient model deployment on servers and devices, minimizing latency, and preserving privacy. The role involves research and development with a track record of publications or product application in efficient deep learning. | 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 |
| Senior Director, Product Management and Marketing, AIML Technologies This role is for a Senior Director of Product Management and Marketing for AIML Technologies at Apple. The individual will set the vision, strategy, and execution for core AI technologies and experiences like Apple Intelligence and Siri, as well as developer and researcher platforms. Responsibilities include owning the strategy, definition, and launch of AI technologies, models, and experiences across the ecosystem, shaping Apple's AI platform strategy, and leading product management and marketing efforts from concept to global launch. The role requires deep expertise in AI, machine learning, and large language models, with a proven track record of executive-level leadership and influencing senior stakeholders. | Ship | 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 Applied ML Scientist – Generative Video This role focuses on researching, designing, and training state-of-the-art generative video models, primarily diffusion-based, with applications for creative users. It involves exploring novel architectures, spatiotemporal modeling, and multi-modal conditioning, aiming for real-world product impact. | Post-train | 9 |
| Principal Applied Researcher Seeking a Senior Applied Researcher with expertise in Generative AI and LLM architectures to influence and implement foundational intelligence capabilities across Apple Services. The role involves architecting, designing, and deploying LLM-powered systems, leading research in areas like representation learning and RAG, driving LLM fine-tuning and evaluation, and exploring advanced methods like parameter-efficient adaptation and multi-agent orchestration. The goal is to build production-grade solutions that advance Apple's reasoning capabilities over text and behavioral signals at scale. | AgentPost-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 |
| AIML - Senior ML Researcher in Foundation Models, Responsible AI Senior ML Researcher in Foundation Models, Responsible AI. Focus on research and application of ML methods for breakthrough user experiences while upholding Apple's values, privacy, and quality standards. Will define and deliver responsible ML technologies, develop methods to train and evaluate foundation models with responsibility and safety in mind, research safety alignment and model robustness, and develop mitigations for safe LLM deployment. | Post-trainAgent | 9 |
| AIML - Machine Learning Research Scientist, Data and ML Innovation Research Scientist role focused on fundamental research of foundation models for scientific domains, involving project definition, method development, experimental design, analysis, interpretation, publication, and applied problem-solving. Collaborates with internal teams. | PretrainPost-train | 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, 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 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 |
| 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 |
| 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 |
| 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 |
| 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 |
| 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 |