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Seattle, Washington, United States Software and Services Description In this role you will be responsible for developing, debugging and maintaining an in-house virtualized infrastructure platform, and evaluating and integrating cutting edge compute hardware:- Design, implement, and optimize virtualized compute offerings on a wide variety of hardware types- Integrate and optimize high-performance virtual networking solutions for custom hardware, including Open vSwitch, DPDK, GPU Direct, and RoCE RDMA technologies- Work extensively with KVM, QEMU, and Linux kernel to efficiently enable functionality within virtual machines, including GPU passthrough and SR-IOV configurations- Evaluate and tune performance of low-latency, high-throughput GPU Direct / RoCE interconnects- Collaborate with cross-functional teams to understand and optimize for critical workloads- Tackle and resolve complex issues across accelerator, 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 Minimum Qualifications 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. Proficiency in high-speed networking, particularly RDMA (e.g., InfiniBand, RoCE), and network performance optimization in virtualized settings Knowledge of advanced virtualization concepts, including nested virtualization, VM live migration, and NUMA optimization Proven distributed systems and operating systems knowledge and experience applying it to build stable, performant, and secure execution environments Preferred Qualifications Expertise in GPU development, including driver integration, configuration, and debugging, as well as hands-on experience with hypervisor GPU passthrough and SR-IOV Familiarity with CUDA libraries and GPU compute frameworks. Experience with CloudStack or similar cloud orchestration platforms. Familiarity with Docker, Kubernetes, and containerization technologies. Experience with distributed GPU workloads and optimizing GPU network performance in multi-node environments. At Apple, base pay is one part of our total compensation package and is determined within a range. This provides the opportunity to progress as you grow and develop within a role. The base pay range for this role is between $171,600 and $302,200, and your base pay will depend on your skills, qualifications, experience, and location. Apple employees also have the opportunity to become an Apple shareholder through participation in Apple’s discretionary employee stock programs. Apple employees are eligible for discretionary restricted stock unit awards, and can purchase Apple stock at a discount if voluntarily participating in Apple’s Employee Stock Purchase Plan. You’ll also receive benefits including: Comprehensive medical and dental coverage, retirement benefits, a range of discounted products and free services, and for formal education related to advancing your career at Apple, reimbursement for certain educational expenses — including tuition. Additionally, this role might be eligible for discretionary bonuses or commission payments as well as relocation. Learn more about Apple Benefits. Note: Apple benefit, compensation and employee stock programs are subject to eligibility requirements and other terms of the applicable plan or program. Apple is an equal opportunity employer that is committed to inclusion and diversity. We seek to promote equal opportunity for all applicants without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, Veteran status, or other legally protected characteristics. Learn more about your EEO rights as an applicant . #J-18808-Ljbffr