Senior Cloud Engineer – Special Projects

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.

You’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.

Description
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.

Responsibilities
Design, build, and maintain scalable cloud infrastructure and services supporting AI-driven products and experiments
Develop data pipelines that process and transform large volumes of multi-modal data
Implement inference platforms that host or proxy models for live inference, batch annotation, and large-scale evaluation
Design and build metrics dashboards, KPIs, and evaluation frameworks to measure data quality, model performance, and system health
Collaborate with data scientists, AI engineers, and platform teams to ensure reliable, traceable, and reproducible insights
Contribute to architecture and design reviews, and set best practices for data integrity, privacy, and secure compute
Work with evolving hardware to help bridge the gap between on-device data and cloud intelligence
Prototype novel approaches to data-driven performance analysis, scaling from experiment to production

Minimum qualifications
Proven experience building distributed backend systems, web services, and data pipelines
Strong proficiency in one or more modern languages such as Python, Go, or Swift
Experience deploying, managing, and optimizing scalable cloud infrastructure on AWS, GCP, or other modern cloud platforms
Experience architecting and orchestrating resilient, distributed applications using Kubernetes or similar container orchestration frameworks
Deep understanding of cloud infrastructure, containerization, and CI/CD automation
Experience designing and operating ETL/ELT pipelines that transform diverse, large-scale data, including device telemetry, logs, or model outputs
Familiarity with data warehousing, SQL/NoSQL systems, and scalable storage architectures
Hands-on experience with data visualization, dash boarding, or metric evaluation frameworks
Strong focus on system reliability, observability, and performance tuning
Ability to collaborate effectively with hardware, user experience, AI, and robotics teams to shape system behavior end-to-end
Bachelor’s or Master’s degree in Computer Science, Data Engineering, or related field, and 5+ years of industry experience

Preferred qualifications
Experience with multi-modal data systems
Background in robotics or simulation pipelines
Familiarity with distributed computation frameworks for workflow orchestration and large-scale data processing
Understanding of model lifecycle management and inference serving architectures
Knowledge of observability tooling and best practices for cloud infrastructure
Strong intuition for data quality metrics, evaluation design, and experiment analysis