Job Description
Summary
The Apple Services Engineering (ASE) organization is responsible for building powerful platforms that enable engineers to deliver incredible experiences to customers.
Join this team, and you'll help us create and deploy systems that support Appleʼs world-renowned hardware and software architecture.
Our compute team is responsible for designing and building the foundational pieces of our in-house cloud technologies. In this role, you will collaborate with teams across Apple to deliver forward-looking high-performance virtual networking technologies for various cloud platforms supporting AIML workload. The successful candidate is highly motivated individual with strong technical, communication, and project management skills to create intuitive user experiences, who is passionate about quality, and meticulous about the details that surprise and delight our customers.
Description
Design, implement, and optimize GPU 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 pass through and SR-IOV configurations.
Develop RDMA solutions and networking optimizations, particularly in relation to GPU workloads, to improve data transfer rates and minimize latency in distributed applications.
Collaborate with multi-functional teams to integrate GPU and RDMA capabilities within cloud frameworks such as CloudStack, improving both compute and network performance.
Tackle and resolve sophisticated issues across GPU, virtualization, and networking layers, ensuring robust performance and stability.
Build and maintain documentation, standard methodologies, and scripts for deployment and management of GPU and RDMA networking in virtualized environments.
Minimum Qualifications
- Bachelorʼs 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, 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.
- Proven programming skills in system programming languages (C/C++) and scripting languages (Python, Bash).
Preferred Qualifications
- 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.