Apple's intelligent systems connect hardware, software, and services in ways that feel effortless and deeply personal. We're looking for an engineer who thrives at this intersection - someone who can design robust cloud infrastructure and services, build intelligent data pipelines, and turn complex, multi-modal data into clear and actionable insights.\\n\\nYou'll architect and operate the systems that power Apple's distributed AI experiences - from data pipelines processing large-scale device and server logs, to inference platforms hosting models for live and offline evaluation. Your work will help teams understand, optimize, and elevate the intelligence that drives Apple products.
Our team works at the intersection of hardware, software, and intelligence. We design the systems, infrastructure, and tools that enable Apple's next generation of AI-driven experiences - from on-device middleware and distributed inference platforms to large-scale data pipelines, interactive analytics, and advanced developer tooling. We collaborate closely with hardware, robotics, ML, design, and platform teams to build end-to-end solutions that are performant, intuitive, and deeply integrated into Apple's ecosystem. The work is hands-on, highly cross-disciplinary, and central to shaping how Apple's intelligent systems evolve.
Proven experience building distributed backend systems, web services, and data pipelines\nStrong proficiency in one or more modern languages such as Python, Go, or Swift\nExperience deploying, managing, and optimizing scalable cloud infrastructure on AWS, Google Cloud Platform, or other modern cloud platforms\nExperience architecting and orchestrating resilient, distributed applications using Kubernetes or similar container orchestration frameworks\nDeep understanding of cloud infrastructure, containerization, and CI/CD automation\nExperience designing and operating ETL/ELT pipelines that transform diverse, large-scale data, including device telemetry, logs, or model outputs\nFamiliarity with data warehousing, SQL/NoSQL systems, and scalable storage architectures\nHands-on experience with data visualization, dash boarding, or metric evaluation frameworks\nStrong focus on system reliability, observability, and performance tuning\nAbility to collaborate effectively with hardware, user experience, AI, and robotics teams to shape system behavior end-to-end\nBachelor's or Master's degree in Computer Science, Data Engineering, or related field, and 5+ years of industry experience
Experience with multi-modal data systems\nBackground in robotics or simulation pipelines\nFamiliarity with distributed computation frameworks for workflow orchestration and large-scale data processing\nUnderstanding of model lifecycle management and inference serving architectures\nKnowledge of observability tooling and best practices for cloud infrastructure\nStrong intuition for data quality metrics, evaluation design, and experiment analysis
Employers have access to artificial intelligence language tools (“AI”) that help generate and enhance job descriptions and AI may have been used to create this description. The position description has been reviewed for accuracy and Dice believes it to correctly reflect the job opportunity.
- Dice Id: 90733111
- Position Id: cac8a7583b4ffd4410034ad41ad7eab1
- Posted 3 hours ago
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