Hardware Systems Engineer Data Center HWE

At Apple new ideas have a way of becoming products services and customer experiences very quickly. Every single day people do amazing things at Apple. Do you want to impact billions of users by developing extraordinary products with a prime focus on accuracy understandability and performance of the product You will become part of a hardware development team that furthers engineering perfection creativity and innovation. Dynamic inspiring people and innovative technologies are the norm here. Bring passion and dedication to your job and theres no telling what you could accomplish.

We are seeking an experienced Server Hardware Engineer with deep expertise in CPU architectures compute performance analysis and cloud-scale hardware this role you will evaluate next-generation server platforms assess workload requirements and guide strategic decisions on processor selection across x86 ARM and accelerator-enabled systems. You will partner closely with SRE platform engineering and capacity planning teams to ensure our Compute cloud infrastructure runs on the most efficient and cost-effective compute platforms.

CPU Architecture u0026 Performance Engineering: Evaluate and compare CPU architectures (Intel AMD ARM emerging accelerators) for cloud and containerized workloads. Conduct microbenchmarking and workload-specific benchmarking (DB caching ML inference microservices network-heavy workloads). Analyze CPU metrics including IPC cache hierarchy behavior NUMA topology SMT/Hyperthreading efficiency turbo behaviors and power/performance curves. Build performance models to predict workload scaling throughput and cost efficiency across CPU Hardware u0026 Platform Analysis: Assess server platforms including memory configurations PCIe topology I/O bandwidth NIC configurations and accelerator integration (GPU SmartNIC DPU). Optimize server configurations for Kubernetes clusters virtualized environments and bare-metal workloads. Collaborate with OEMs and silicon vendors on roadmap evaluations and feature u0026 Kubernetes Workload Profiling: Profile and analyze workload patterns across large-scale distributed systems. Evaluate CPU/memory utilization trends to identify bottlenecks over-provisioning or scaling inefficiencies. Provide input into cluster sizing autoscaling strategies and capacity planning based on real workload telemetry. Build dashboards and telemetry pipelines to visualize compute efficiency across u0026 Cost Optimization: Lead CPU and server platform recommendations for procurement cycles. Model TCO (total cost of ownership) including performance per watt performance per dollar and rack-level density. Provide guidance on the right mix of CPU SKUs instance types and server configurations for various cloud services.

Bachelors or Masters degree in Electrical Engineering Computer Engineering Computer Science or related technical field.n5 years of experience in server hardware engineering CPU architecture evaluation or performance understanding of microarchitecture concepts:nPipelines branch prediction out-of-order executionnCache hierarchies (L1/L2/L3) prefetching NUMAnSMT/hyperthreading core utilization turbo boost behaviorsnExperience evaluating and comparing Intel Xeon AMD EPYC and -on experience with Kubernetes cloud workloads virtualization (KVM) and container in benchmarking tools (SPEC fio sysbench perf pmu-tools) and workload with telemetry and observability stacks (Prometheus Grafana eBPF etc.).

Experience with large-scale cloud providers hyperscalers or high-performance computing (HPC) in power/performance tuning BIOS optimization and firmware-level of CPUs SmartNICs GPUs and offload/acceleration building internal performance dashboards and analytics ability to thrive in a fast-paced dynamic and often ambiguous relentless commitment to quality and user problem-solving skills and the ability to debug complex issues across multiple layers of a communication and interpersonal skills with the ability to articulate complex technical concepts to both technical and non-technical to thrive in a fast-paced dynamic environment and manage multiple priorities effectively.