Job 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. 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 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

Requirements

Must-haves

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
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

Nice-to-haves

None flagged.

Application prep

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Keywords to mirror

aimlpythongoswiftawsgcpkubernetesci/cdsql

Platform: apple
Effort: medium