Lead AI Accelerator Performance Architect

Engg; Sunnyvale (CA); On-site; USD 175,000 - 275,000; Full time

Job summary

Cerebras Systems is seeking a Senior Staff AI Accelerator Performance Architect in Sunnyvale, CA. You will connect workloads to architectural behavior, identify bottlenecks, and influence hardware and software roadmaps through rigorous performance analysis.

This role requires deep knowledge of hardware architecture and modeling, simulation, or RTL validation; you will collaborate with architecture, compiler, kernel, and systems teams to deliver trusted workload insights.

Qualifications

• 7+ years of experience in performance analysis, performance modeling or architecture exploration.
• Strong understanding of hardware architecture developed through hardware, compiler, kernel, runtime or system-performance work.
• Experience developing analytical, simulation-based or trace-driven performance models using Python, C++ or similar environments.
• Ability to communicate modeling assumptions, uncertainty, bottlenecks and recommendations clearly.

Responsibilities

• Own and evolve performance models and methodologies for next-generation accelerator and system architectures.
• Build and extend analytical, simulation-based or trace-driven models across workloads, architectural features and product generations.
• Analyze important AI workloads, from kernels to end-to-end inference/training, to identify bottlenecks and opportunities.
• Evaluate architectural features and their expected performance return across workloads.
• Partner with architecture, compiler, kernel, runtime and systems teams to evaluate mappings and optimizations.

Skills

Performance analysis

Performance modeling

Hardware architecture

Python

C++

Quantitative analysis

Communication

Education

MS or PhD in Electrical Engineering, Computer Engineering, Computer Science

Tools

RTL simulation

FPGA prototypes

Emulation

Job description

Cerebras Systems is seeking a Senior Staff AI Accelerator Performance Architect in Sunnyvale, CA. You will connect workloads to architectural behavior, identify bottlenecks, and influence hardware and software roadmaps through rigorous performance analysis.

This role requires deep knowledge of hardware architecture and modeling, simulation, or RTL validation; you will collaborate with architecture, compiler, kernel, and systems teams to deliver trusted workload insights.