Senior AI Infrastructure Architect (Multicloud)

Apple Inc.; Cupertino (CA); On-site; USD 311,000 - 497,000; Full time

Benefits offered by this job

Stock options

Comprehensive medical coverage

Retirement benefits

Educational reimbursement

Job summary

Apple Inc. seeks a Distinguished Engineer to lead the design and evolution of next-generation AI infrastructure.

You will shape architecture and strategy for large-scale training and inference, spanning multi-cloud compute fleets and accelerator platforms. You’ll collaborate with ML researchers, software engineers, and cross-functional partners to scale performance and reliability across the stack—hardware, software, and cloud infrastructure.

Qualifications

• Bachelor's degree in CS or related field.
• 15 years of experience designing and building very large-scale distributed systems.
• Proficiency in at least 1 backend language (Python, C++, Go, Rust).
• Proficiency with cloud-native architectures and Kubernetes.
• Hands-on experience with ML accelerators such as GPUs and TPUs.

Responsibilities

• Set the technical vision and roadmap for frontier AI infrastructure across a multi-cloud compute fleet.
• Design and build distributed systems for job scheduling, cluster management, and cost governance.
• Partner with ML researchers and engineers to optimize end-to-end performance of training and inference workloads.
• Collaborate with cross-functional teams across cloud infra, finance, and engineering to align strategy.

Skills

Large-scale distributed systems

Backend languages

Kubernetes

ML accelerators

Mentoring engineers

Education

Bachelor's degree

Master's or PhD preferred

Tools

PyTorch

JAX

Job description

Apple Inc. seeks a Distinguished Engineer to lead the design and evolution of next-generation AI infrastructure.

You will shape architecture and strategy for large-scale training and inference, spanning multi-cloud compute fleets and accelerator platforms. You’ll collaborate with ML researchers, software engineers, and cross-functional partners to scale performance and reliability across the stack—hardware, software, and cloud infrastructure.