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Apple Cloud Infrastructure Engineer - GPU United States, Washington, Seattle 886796746
Today
Apple Service Engineering (ASE)’s Compute team is seeking an experienced software engineer to build and enhance internal cloud infrastructure offerings. You will be responsible for core components of this groundbreaking platform, integrating the latest cloud hardware technologies with Apple’s own hardware and software. In this role, you will collaborate with teams across Apple to deliver forward-looking high-performance virtualized infrastructure, supporting everything from LLM model training to maximum-security confidential computing environments. You will partner with internal application teams to understand their requirements, co-design operating system features and datacenter infrastructure to meet your needs, and look ahead at emerging technologies to incorporate them into our services.
In this role you will be responsible for developing, debugging and maintaining an in-house virtualized infrastructure platform, and evaluating and integrating groundbreaking compute hardware:- Design, implement, and optimize GPU Compute and high-performance networking solutions, ensuring seamless integration and high throughput in virtualized environments- Work extensively with KVM, QEMU, and Linux kernel modifications to enable GPU functionality within virtual machines, including GPU passthrough and SR-IOV configurations- Evaluate and tune performance of low-latency, high-throughput GPU Direct / RoCE interconnects- Address and resolve complex issues across GPU, virtualization, and networking layers, ensuring robust performance, stability, and security- Research and prototype new hardware and datacenter architectures to stay at the forefront of the industry
- At least 5+ years and Bachelor’s Degree in Computer Science, or equivalent related experience.
- 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, configuration, and debugging, as well as hands-on experience with hypervisor GPU passthrough and SR-IOV.
- Proficiency in high-speed networking, particularly RDMA (e.g., InfiniBand, RoCE), and network performance optimization in virtualized settings.
- Programming skills in system programming languages (C/C++) and scripting languages (Python, Bash).
- Familiarity with CUDA libraries and GPU compute frameworks.
- Experience with CloudStack or similar cloud orchestration platforms.
- Knowledge of advanced virtualization concepts, including nested virtualization, VM live migration, and NUMA optimization.
- Familiarity with Docker, Kubernetes, and containerization technologies.
- Experience with distributed GPU workloads and optimizing GPU network performance in multi-node environments.
Note: Apple benefit, compensation and employee stock programs are subject to eligibility requirements and other terms of the applicable plan or program.
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