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 there's no telling what you could accomplish.

Description

We are seeking an experienced Server Hardware Engineer with deep expertise in CPU architectures, compute performance analysis, and cloud-scale hardware optimization. In 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.","responsibilities":"CPU Architecture & 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 generations.

Server Hardware & 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 testing.

Cloud & 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 clusters.

Procurement & 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.

Preferred Qualifications

Experience with large-scale cloud providers, hyperscalers, or high-performance computing (HPC) environments.

Expertise in power/performance tuning, BIOS optimization, and firmware-level configuration.

Knowledge of CPUs, SmartNICs, GPUs, and offload/acceleration architectures.

Experience building internal performance dashboards and analytics tools.

Demonstrated ability to thrive in a fast-paced, dynamic, and often ambiguous environment.

Passionate, relentless commitment to quality and user experience.

Strong problem-solving skills and the ability to debug complex issues across multiple layers of a system.

Excellent communication and interpersonal skills, with the ability to articulate complex technical concepts to both technical and non-technical audiences.

Ability to thrive in a fast-paced, dynamic environment and manage multiple priorities effectively.

Minimum Qualifications

Bachelor's or Master's degree in Electrical Engineering, Computer Engineering, Computer Science, or related technical field.

5+ years of experience in server hardware engineering, CPU architecture evaluation, or performance engineering.

Strong understanding of microarchitecture concepts:

Pipelines, branch prediction, out-of-order execution

Cache hierarchies (L1/L2/L3), prefetching, NUMA

SMT/hyperthreading, core utilization, turbo boost behaviors

Experience evaluating and comparing Intel Xeon, AMD EPYC, and ARM.

Hands-on experience with Kubernetes, cloud workloads, virtualization (KVM), and container infrastructure.

Proficiency in benchmarking tools (SPEC, fio, sysbench, perf, pmu-tools) and workload profiling.

Familiarity with telemetry and observability stacks (Prometheus, Grafana, eBPF, etc.).

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 .