About the role

What will you do at Apple?

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.

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

Which skills does this role require?

Distributed SystemsData PipelinesPythonGoSwiftAWSGCPKubernetesCI/CDETL/ELTSQL/NoSQLData VisualizationSystem ReliabilityPerformance TuningCloud EngineeringAIContainerizationETLELTSQLNoSQLData WarehousingTelemetrySimulation PipelinesModel Lifecycle ManagementWorkflow OrchestrationData Quality MetricsBackend SystemsMachine Learning

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