Currently tracking 171 active AI roles, down 37% versus the prior 4 weeks. Primary focus: Agent · Engineering. Salary range $120k–$487k (avg $235k).
Apple has 261 active AI-related job listings. The majority of these roles are focused on agents, accounting for 24% of the total, followed by application (22%) and serving infrastructure (21%). Engineering is the primary function for these positions, with the United States being the dominant hiring country. Frequent tech tags include model serving, inference infrastructure, and LLM observability. Over the last 30 days, Apple has posted 111 new AI roles, representing a 61% increase compared to the previous 30-day period.
Apple currently has 233 active AI-related roles in our index. The most common open titles are: Machine Learning Engineer (4), AIML - Sr Data Scientist, Evaluation (2), Advanced Manufacturing Engineer(iPhone) - Smart Manufacturing (2), Machine Learning Engineer, Apple Services Engineering (2), Machine Learning Software Engineer (2). Most positions are in Engineering and Research.
Apple's active AI hiring is concentrated in: agents (30%), application (21%), serving infrastructure (14%). These categories follow a seven-stage AI lifecycle: data, pre-training, post-training, serving infrastructure, agents, evaluation, and application.
Apple is hiring AI talent in: United States (182 roles), China (17 roles), India (10 roles), United Kingdom (7 roles).
Job postings at Apple most frequently mention: Machine Learning, Python, Data Science, Large Language Models (LLMs), Statistics.
In the past 30 days, Apple has posted 80 new AI-related roles.
| Title | Stage | AI score |
|---|---|---|
| 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. |
| 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 |
| 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 |
| 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 |
| 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 |
| Machine Learning Engineer, Computer Vision - Strategic Data Solutions Machine Learning Engineer specializing in Computer Vision for fraud detection within Apple's Strategic Data Solutions team. The role involves building end-to-end solutions, curating datasets, training models, and deploying them into a real-time platform to combat fraud, waste, and abuse. | ShipData | 8 |
| AI/Machine Learning Engineer AI/ML Engineer to build intelligent systems and deploy state-of-the-art AI models and systems across Apple's business groups. Responsibilities include implementing ML infrastructure, developing feature engineering and fine-tuning frameworks, designing ML pipelines, and optimizing models. The role requires designing systems from raw data to autonomous action, implementing RAG pipelines, working with embeddings and vector databases, building AI agents with tool use, and fine-tuning transformer models. Experience with large-scale data and ML frameworks is essential. | AgentData | 8 |
| Machine Learning Research Engineer, Generative AI Machine Learning Research Engineer focused on applying generative AI and ML to create innovative user experiences for hundreds of millions of users across Apple platforms. The role involves the full development cycle from ideation to productization, covering areas like handwriting and text recognition, synthesis, document understanding, and freeform drawing generation, with a focus on computer vision, speech recognition, deep learning, and multimodal LLMs. | ShipPost-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 |
| Senior Machine Learning Engineer, Search & AI Senior Machine Learning Engineer focused on developing next-generation Search and Question Answering systems using cutting-edge search technologies and large language models. The role involves improving Query Understanding, Retrieval, and Ranking, leveraging fine-tuning, reinforcement learning, embeddings, deep learning, and online learning. Experience with RAG, retrieval, and generative LLMs is crucial. | AgentServe | 8 |
| Staff Machine Learning Engineer – Ads Signals Intelligence & Information Retrieval Staff Machine Learning Engineer at Apple Ads focused 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, enabling privacy-aware decision-making. Key activities include LLM fine-tuning, knowledge graph construction, semantic search, and multimodal representation learning to extract structured intelligence from unstructured data, supporting ad retrieval, creative ranking, and marketplace optimization. | AgentServe | 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 |
| AIML - Applied ML Engineer, Responsible AI This role focuses on designing, building, and deploying production-grade ML models for abuse detection across multiple modalities (text, image, audio) to protect Apple's ecosystem. It involves owning the full ML lifecycle, driving data strategy, architecting monitoring systems, and collaborating with cross-functional teams to deliver security solutions. | ShipPost-train | 8 |
| Sr. Machine Learning Engineer The role focuses on enhancing Siri and Apple products using generative AI and LLMs, with a strong emphasis on applied machine learning and software engineering. Key responsibilities include developing and improving generative experiences, creating evaluation techniques for model responses, and contributing to search relevance. The role also involves mentoring and collaborating with various teams. | ShipEval Gate | 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 within Apple's consumer products. Responsibilities include data collection, model architecture design, training custom models, and partnering with cross-functional teams to integrate these features from concept to delivery. The ideal candidate has significant industry experience in computer vision and machine learning, with hands-on experience in building, training, evaluating, and deploying various model types, particularly vision models. | Ship | 8 |
| Senior Staff Machine Learning Engineer – Ads Prediction, Signals & Quality Senior Staff Machine Learning Engineer at Apple Ads, focusing on innovation in ad prediction, quality, and privacy-preserving signals. The role involves building large-scale prediction models, designing privacy-respecting signals, and ensuring ad quality. It requires expertise in deep learning, prediction systems, and privacy-preserving ML, with a strong emphasis on production experience and technical leadership. | AgentData | 8 |
| Software Engineer in Natural Language Processing (NLP) and Machine Learning (ML) Software Engineer focused on building and productizing Generative AI experiences using NLP and ML for Apple platforms. The role involves research, development, and deployment of ML/NLP technologies, with a focus on on-device and private compute cloud applications. | ShipPost-train | 8 |
| Machine Learning Engineer Machine Learning Engineer on the Answers & Knowledge & Information team at Apple, focusing on improving Siri, Spotlight, and Safari search features. This role involves large-scale ML/DL for query understanding and ranking, using word embeddings, deep learning, and online learning on petabytes of data from millions of users. The engineer will design and build infrastructures, perform language and user intent analysis, process web-scale data, and run evaluations. | ShipAgent | 8 |
| Senior Machine Learning Engineer - AI, Search & Knowledge (ML Hub Core) Senior ML Engineer at Apple focused on building infrastructure and tools for the GenAI lifecycle, from experimentation to production inference, emphasizing observability, reproducibility, and modularity. The role involves contributing to architectural direction and designing for flexibility across future projects, with a strong focus on scalable data/compute infrastructure. | ServeAgent | 8 |
| AIML - Sr Backend Engineer, Data and ML Innovation This role focuses on building scalable backend pipelines and services for training data used in Foundation Models and Apple Intelligence features. Responsibilities include converting raw data into training formats, processing and filtering large datasets, and developing APIs for data access. The role also involves large-scale inferences for pre-training and post-training using fine-tuned LLMs. | DataPost-train | 8 |
| AI Data Scientist This role focuses on evaluating, optimizing, and analyzing the performance of ML and multi-modal LLMs. The Data Scientist will develop metrics, conduct failure analysis, process data for evaluation, and implement optimization techniques. They will collaborate with cross-functional teams to integrate models and communicate results. The role requires experience with model evaluation, RAG, and LLM prompt evaluation, with preferred experience in multi-modal foundation models and GenAI frameworks. | Eval GatePost-train | 8 |
| Perception Algorithm Engineer This role focuses on designing and implementing real-time multi-object tracking systems using deep learning and multimodal estimates for computer vision problems within Apple products. It involves developing evaluation frameworks, curating datasets, and integrating perception systems into a larger software stack, with a strong emphasis on robotics and state-estimation pipelines. | AgentData | 7 |
| AIML - Sr Data Scientist, Evaluation This role focuses on developing and researching evaluation methods to improve the quality of user-facing AI products like Siri and Apple Intelligence. It involves working with large datasets, applying advanced analytical methods including prompt engineering and using LLMs as judges, and partnering with engineering teams to translate methodological developments into production technologies. The goal is to guide product development and decisions through rigorous evaluation and data analysis, ultimately impacting products used by hundreds of millions globally. | Eval GatePost-train | 7 |
| Senior Machine Learning Engineer, Analytics & Data Engineering Senior Machine Learning Engineer focused on building and innovating AI/ML foundations for Apple's services, ensuring security, privacy, and scalability. The role involves researching and developing state-of-the-art AI/ML solutions, designing secure and performant systems, and collaborating with broader teams. Requires strong engineering foundations, experience with distributed systems, and modern AI/ML frameworks. | Serve | 7 |
| Software Development Engineer, Intelligence Platform - Proactive Software Development Engineer role focused on building the on-device intelligence platform for Apple products, powering Generative AI experiences like Apple Intelligence. Responsibilities include developing knowledge serving sub-systems, APIs, and on-device data processing runtime and storage, shipping code that runs on millions of devices. | Serve | 7 |
| Senior Machine Learning Engineer - Ads Relevance & Quality Senior Machine Learning Engineer at Apple Ads focusing on Ads Relevance & Quality. The role involves designing and implementing ML models, particularly NLP and multi-modal models, to evaluate ad relevance, detect inappropriate content, and optimize user satisfaction. It requires experience with Transformer-based architectures, fine-tuning LLMs, and large-scale ML deployment in domains like ad tech or content moderation. | Post-train | 7 |
| Software QA Engineer - Automation, Siri Software QA Engineer focused on automation for Siri, Apple's AI assistant. The role involves ensuring software frameworks and environments are updated for new AI capabilities and hardware platforms, partnering with development teams, and owning automation support. It requires expertise in Python, Bash, or Swift with ML/NLP libraries, developing test plans, and building robust testing frameworks using machine learning models and LLMs. | Ship | 7 |
| Software QA Engineer - Automation, Siri Software QA Engineer focused on automation for Siri, Apple's AI assistant. The role involves ensuring software frameworks and environments are updated for new AI capabilities, partnering with development teams, and owning automation support. Requires expertise in Python, Bash, or Swift with ML/NLP exposure, and experience building test frameworks using ML models and LLMs. | Agent | 7 |