Software Engineer role focused on building tools and systems for the automatic evaluation of Apple's AI products, specifically using LLM-as-judge and related technologies to improve the quality and efficiency of these evaluations. The role involves designing and developing frameworks, pipelines, and tools for AI model development, deployment, and measurement, directly impacting product launch decisions.

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.

Machine Learning Engineer focused on localizing and scaling LLMs and NLP models for Apple's international customers. The role involves end-to-end model development, including training, experimentation, evaluation, and deployment, with a focus on data-driven quality programs and building tools for software translation.

This role focuses on operationalizing machine learning models for recommendations and personalization systems at Apple. The primary responsibility is building and managing real-time and batch inference pipelines, optimizing system performance, and driving experimentation. The role bridges research and production by developing infrastructure, tooling, and monitoring for shipping ML-driven features. It involves partnering with ML researchers, designing inference services, building data pipelines, developing deployment and evaluation tooling, leading A/B testing, and collaborating on observability and system reliability. While the core is inference (L3), the mention of agents and LLMs in preferred qualifications suggests a secondary focus on agentic systems (L4).

Machine Learning Engineer to join the Ads Relevance and Quality team, responsible for building intelligent systems to evaluate ad relevance, detect low-quality or offensive content, and optimize user satisfaction using applied ML, NLP, and content quality techniques.

Manager for Responsible Development & Safety in Apple Services Engineering, focusing on shaping policies, evaluating AI models and applications, and ensuring safe deployment of user-facing features. The role involves leading a team, collaborating with various cross-functional teams, and developing evaluation processes for AI/ML models.

This role focuses on designing and implementing evaluation frameworks for AI/ML systems, specifically for Apple's consumer-facing products. The Data Scientist will work with large datasets, develop methodologies for assessing product quality, and partner with engineering teams to improve user experience and guide feature development. The role involves building evaluation datasets, human-in-the-loop systems, and translating insights into actionable recommendations.

This role focuses on applying machine learning and computer vision to industrial problems in manufacturing, specifically for inspection equipment. The engineer will develop and deploy ML models to judge millions of units daily, identify patterns and anomalies in data, and build toolkits for applying ML and statistical tools. Responsibilities include data analysis, software development in Python/Java/C++, and working with inspection systems. The role requires strong ML/CV experience in industrial settings, proficiency in Python and ML algorithms, and experience with image processing. It involves developing solutions from inception to production, with a focus on shipping AI-powered products for quality control in manufacturing.

Seeking an experienced AI/ML Security Engineer to design and implement security frameworks for AI/ML pipelines, conduct security assessments, develop automated testing and monitoring, lead incident response, and establish secure MLOps practices. The role also involves strategic business leadership, translating risks, developing roadmaps, and collaborating with cross-functional teams.

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.

This role focuses on building and scaling cloud-native ML infrastructure, specifically platforms for ML training and inference. It involves designing and implementing agentic workflows, Kubernetes-based control planes, and infrastructure servers to manage these systems at a large scale. The role emphasizes open-source contributions and expertise in Kubernetes and Crossplane.

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.

Internship role focused on software engineering and natural language processing within the Siri & Information Intelligence team at Apple. The intern will collaborate with experts, receive mentorship, and work on developing technologies and experiences for the next generation of Siri products.

Senior Machine Learning Platform Engineer at Apple, focused on building and scaling the AI, Search & Knowledge platform. This role involves creating seamless integrations between ML frameworks and the platform, designing Python SDKs and APIs, and building backend services to support model management and serving infrastructure. The goal is to enable ML practitioners to focus on innovation by abstracting infrastructure complexity.

Machine Learning Engineer role focused on improving search quality for Apple Maps using Generative AI and LLMs at scale. Requires experience delivering ML-driven products and strong programming skills.