CPU Performance & Workload Architect

Apple Inc.; Santa Clara, Northern (CA, KY); Hybrid; USD 129,000 - 225,000; Full time

Benefits offered by this job

Employee stock plan

Apple benefits and relocation support

Job summary

Apple Inc. in Santa Clara, California, is seeking an experienced CPU Performance & Workload Analysis Engineer within Platform Architecture. You will bridge hardware and software teams to optimize CPU designs and guide roadmaps for next-generation SoCs.

The role emphasizes profiling workloads, building analysis tools, and collaborating across CPU, system, and software groups to translate workloads into hardware advances.

Qualifications

• Experience with CPU architecture and micro-architecture.
• Objected-oriented programming experience with C and C++.
• Experience with CPU performance analysis and associated tools.

Responsibilities

• Profile and analyze existing and emerging workloads, bring up in CPU/SOC simulation environment.
• Develop and maintain performance and trace analysis tools.
• Develop and implement visual extensions to assist with data analysis that can be used internally and also by the various software partners in Apple.
• Run and analyze workloads on simulators and prototype devices as well as work on developing and automating performance analysis infrastructure.
• Develop domain expertise in emerging fields (ex: ML, AR/VR) in order to both identify hardware advancement opportunities and assist software teams in optimizing for our devices.
• Profile and analyze workload in potential new product areas to help guide CPU roadmap decisions.

Skills

CPU architecture

C & C++

CPU performance analysis

Education

MS in Electrical or Computer Engineering

Job description

Apple Inc. in Santa Clara, California, is seeking an experienced CPU Performance & Workload Analysis Engineer within Platform Architecture. You will bridge hardware and software teams to optimize CPU designs and guide roadmaps for next-generation SoCs.

The role emphasizes profiling workloads, building analysis tools, and collaborating across CPU, system, and software groups to translate workloads into hardware advances.