Cloud Networking Engineer - GPU

$135,400 - $250,600/Yr

Apple - Seattle, WA

Full-time - Mid Level

Seattle, WA

Computer and Electronic Product Manufacturing

About the position

The Apple Services Engineering (ASE) organization is seeking a dedicated individual to join their compute team, responsible for developing and maintaining virtual networking software solutions for GPUs across various cloud platforms. This role involves collaboration with multiple teams to deliver high-performance virtual networking technologies that support AIML workloads, ensuring seamless integration and high throughput in virtualized environments.

Responsibilities

• Develop, debug, and maintain virtual networking software solutions for GPUs.
• Design, implement, and optimize GPU and high-performance networking solutions.
• Work with KVM, QEMU, and Linux kernel modifications to enable GPU functionality within virtual machines.
• Develop RDMA solutions and networking optimizations for GPU workloads.
• Collaborate with multi-functional teams to integrate GPU and RDMA capabilities within cloud frameworks.
• Resolve complex issues across GPU, virtualization, and networking layers.
• Build and maintain documentation and scripts for deployment and management of GPU and RDMA networking.

Requirements

• Bachelor's Degree in Computer Science or related field.
• 5+ years of experience in virtualization, specifically with KVM and QEMU.
• Strong Linux development background, including kernel-level development and tuning for high-performance GPU and networking workloads.
• Expertise in GPU development, including driver integration and debugging.
• Proficiency in high-speed networking, particularly RDMA (e.g., InfiniBand, RoCE).
• Proven programming skills in system programming languages (C/C++) and scripting languages (Python, Bash).

Nice-to-haves

• Familiarity with CUDA libraries and GPU compute frameworks.
• Experience with CloudStack or similar cloud orchestration platforms.
• Knowledge of advanced virtualization concepts, including nested virtualization and VM live migration.
• Familiarity with Docker, Kubernetes, and containerization technologies.
• Experience with distributed GPU workloads and optimizing GPU network performance.

Benefits

• Comprehensive medical and dental coverage.
• Retirement benefits.
• Discounted products and free services.
• Reimbursement for certain educational expenses, including tuition.
• Discretionary bonuses or commission payments.
• Relocation assistance.