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.

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.

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.

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.

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.

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.

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.

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.

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.

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.

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.

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.

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.

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.

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.

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.

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.

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.

Senior Machine Learning Engineer in Finance at Apple, focused on building and extending AI/ML platforms and services for finance organizations. The role involves developing infrastructure for generative AI, agentic workflows, and ML inference, with a strong emphasis on MLOps, observability, and compliance within Finance governance frameworks.

This role focuses on building AI systems and algorithms to automate crash debugging and root-cause analysis for firmware boot failures in cellular modem chips. The engineer will develop AI-powered engineering tools, LLM APIs, AI agents, and automated workflows, leveraging AI for intelligent automation in silicon bring-up and validation.

This role focuses on enabling Finance teams to transform from manual data preparers to AI-enabled decision partners. The Finance Data Scientist will guide teams through a maturity journey from automation to AI and predictive models, empowering them to leverage capabilities like data automation, BI, advanced analytics, ML, and AI agent creation within a governed framework. Responsibilities include partnering with leaders, developing roadmaps, educating teams on concepts like prompt engineering and agentic AI design, collaborating on solutions like automated workflows and finance-specific AI agents, and championing governance and AI frameworks.

This role focuses on designing and optimizing conversational AI experiences for Apple's online store, aiming to enhance customer engagement and satisfaction. The designer will lead the conceptualization and implementation of chatbot conversations, leveraging technologies like RAG and AI QA tools, and ensuring brand voice consistency. The role requires a blend of creativity, strategic thinking, and technical understanding of how AI models retrieve information and generate responses.

This role focuses on applying Generative AI and machine learning techniques to financial planning and analysis (FP&A) within the APAC region. The analyst will own core FP&A responsibilities, build intelligent data products to transform financial workflows, and leverage LLMs/GenAI frameworks for finance use cases. The role requires strong data fluency, experience with modern data science tools, and the ability to work with incomplete data to generate insights.

Software Engineer to design and build intelligent tooling, automation, and AI-powered workflows using AI agents to improve engineering productivity and software quality across Apple's media technology stack. This role involves prototyping and productizing systems that leverage agentic coding workflows, AI-driven code analysis, and automation pipelines to streamline development processes, accelerate issue resolution, and enhance code quality at scale.

This role focuses on developing and implementing next-generation automated processes for cosmetic and protective finishes (PVD coatings, Ink Printing) in high-volume manufacturing. It involves both physical automation (robotics, PLCs) and digital automation, including machine vision and deploying ML/AI models for predictive maintenance, defect detection, and process optimization. The role requires integrating automation parameters with materials chemistry and collaborating with cross-functional teams.

Staff AI Software Engineer for Siri Core Modeling at Apple, focusing on the on-device software platform for Apple Intelligence. The role involves leading design and development of features, implementing performant code, identifying architectural changes, optimizing performance, and developing software that interfaces with LLMs and on-device intelligence to enhance Siri capabilities. The position also emphasizes leveraging LLMs and AI assistants for engineering productivity.

This role is for an AI Solutions Lead responsible for designing and driving the delivery of enterprise-scale Generative AI and Data Platform solutions within Apple's enterprise. The role involves close collaboration with business stakeholders, hands-on prototyping, and guiding teams through execution to deliver impactful AI solutions.

Machine Learning Engineer focused on GenAI applications, delivering projects end-to-end from conceptualization to deployment. The role involves statistical analysis, business intelligence solutions, and presentations to executives. It requires experience with LLMs/LMMs, agents, agentic workflows, and RAG applications.

Tech Lead Machine Learning Engineer for Finance Digital Transformation at Apple. The role focuses on building data foundations, services, and platforms for insights and automated decisions within the Finance organization, specifically for product cost. Responsibilities include technical leadership, operationalizing AI solutions from prototype to production, and instilling ML engineering practices. Requires experience in ML algorithms, generative AI, agentic solutions, MLOps/LLMOps, data pipelines, and Python.

Tech Lead Machine Learning Engineer for Finance at Apple, focusing on building and operationalizing AI solutions for product cost analysis and decision automation. The role involves leading engineers, collaborating cross-functionally, and bridging the gap between ML prototypes and production systems within the Finance organization. Requires experience in ML algorithms, generative AI, agentic solutions, MLOps, and scalable data pipelines.

Senior Product Data Scientist role focused on driving data-driven strategy and delivering ML and experimentation solutions for Apple's App Store. The role involves applying advanced ML causal inference techniques, developing and deploying ML models for customer insights, and leveraging LLMs/GenAI tools. It requires strong expertise in causal inference, experimentation frameworks, and influencing cross-functional roadmaps.

Senior Software Architect for Siri Attention and Invocation team, focusing on designing and implementing software systems for natural and conversational interactions with virtual assistants using AI/ML technologies, including LLMs and conversational AI. The role involves architecting ML-driven user experiences, integrating with sensory and system software, and optimizing on-device runtime performance.

Software Engineer focused on building and managing internal security services that leverage AI technologies to identify and remediate security risks within the software development lifecycle. The role involves assessing AI-specific security risks and implementing controls, with a preference for experience in LLM-powered solutions.

This role is for a Creative Technologist in Apple's Marcom team, focusing on R&D and prototyping of innovative experiences using emerging technologies like generative AI, LLMs, diffusion models, and agents. The role involves coding, research, experimentation, and collaboration to integrate these technologies into internal workflows and customer-facing experiences.

This role focuses on building AI-assisted systems to analyze CI build and test failures, transforming raw data into actionable insights for OS engineers. The engineer will design and implement AI-powered workflows for failure summarization, pattern identification, and distinguishing signal from noise, integrating AI capabilities into developer tools to accelerate the software development process.

Product Manager for Generative AI within Apple's Ai & Data Platforms team, focusing on building and scaling GenAI capabilities for enterprise use cases like knowledge discovery, conversational AI, and workflow automation. The role involves defining product strategy, working closely with engineering and data science, and ensuring AI is trustworthy, governable, and reliable at scale. Requires a technical background, ability to prototype, and experience shipping AI/ML products.

This role leads the product engineering and building efforts for AI-driven tools within a legal tech ecosystem, focusing on rapid development, prototyping, and delivering legal-contextualized AI applications and features embedded into existing legal workflows. The role involves managing a team, building upon internal AI platforms, and bridging the gap between AI capabilities and business needs.

Machine Learning Engineer focused on Trust and Safety for communication apps, protecting against spam and abuse. The role involves building ML tooling for the entire ML lifecycle, from data ETL and model training to evaluation and deployment, with a strong emphasis on anti-fraud and anomaly detection, particularly in the context of LLMs. The goal is to deliver reusable tooling and integrate with existing systems to enhance customer safety and mitigate attack vectors.

This role is for an AI Solutions Engineer in Apple's Innovation Lab, focusing on helping enterprise customers build applications on Apple platforms using AI and Spatial Computing. The role involves consulting, architecting, building demonstrations, and evangelizing best practices for AI-powered enterprise applications. Requires expertise in LLMs, RAG, traditional ML, and Apple platform development.

Senior Machine Learning Engineer to join the Predictions group, focusing on building core ML models for ad predictions and monetization across Apple's App Store and News platforms. The role involves designing and implementing ML models for user interaction, CTR, and CVR prediction, developing retrieval algorithms, and contributing to modeling areas like deep neural networks, contextual bandits, multi-task learning, and LLM-based ranking signals. It also requires working with large-scale datasets, collaborating with cross-functional teams, and running experiments. Experience with ad tech, recommender systems, or web-scale search/retrieval is preferred, along with deep expertise in neural network architectures and training pipelines.

This role focuses on building APIs for AI models within Apple's Swift Frameworks team. The engineer will implement features, design APIs, and be involved in the full development lifecycle from research to testing and documentation. Collaboration with ML researchers and systems engineers is key.

This role focuses on building the backbone of an AI-powered developer platform that uses AI agents and autonomous workflows to support app development within Apple. The engineer will design and maintain backend services and orchestration systems for multi-agent AI workflows, integrate LLMs into developer tools, and work on cloud deployments and MLOps.

Senior Software Engineer to design and build intelligent tooling and automation using AI-driven agents to improve engineering productivity and content operations. The role involves prototyping and productionizing systems that leverage agentic coding workflows and AI-driven content processing to streamline development and publishing processes.

This role focuses on building and scaling automated insight pipelines for the sales organization, developing ML models for opportunity detection and performance diagnosis, and embedding these insights into AI agents, dashboards, and GenAI tools. The role involves end-to-end insight development, including data preparation, statistical analysis, LLM prompt engineering, and deploying ML models for forecasting, anomaly detection, attribution, and causal inference. It also includes building RCA and recommendation engines, analyzing agent interactions, implementing LLM evaluation pipelines, and supporting experimentation. The role requires partnering with AI engineers and PMs, acting as a data translator, influencing upstream data model design, and driving KPI definitions.

Software Engineer role focused on developing and delivering AI/ML solutions for Apple's hardware product line, including agentic systems and RAG architectures, with responsibilities spanning training, evaluation, and inference pipelines.

Senior Software Engineer focused on building AI-enabled observability solutions for Apple's AI, Search, and Knowledge Platform. The role involves designing and developing user-facing observability features for AIML products and infrastructure, leveraging AI/ML for AIOps, and working with LLMs, ML frameworks, and agentic AI concepts. The position emphasizes building scalable, cloud-native distributed systems and microservices, with a focus on anomaly detection, incident detection, and root-cause analysis within AI observability.

Staff Software Engineer to advance Manufacturing Systems and Operations using LLMs, from prototyping to production and scaling. This role involves working with various organizations to develop impactful solutions, some standalone and others integrated into existing systems.

Senior Full-Stack Engineer role at Apple focused on building web and native applications for security platforms. The role involves partnering with users, owning feature development, and applying generative AI to enhance development processes and features, specifically mentioning agentic workflows and LLMs for data analysis.