Performance Modeling Architect – AI Systems
Summary
Designs and builds system-level performance models and simulations for AI workloads and hardware, analyzing bottlenecks to guide AI compute architecture decisions.
You will develop system-level performance models and simulation frameworks for AI workloads and compute architectures. You will model SoC components, software runtime behavior, memory systems, and interconnects, analyze bottlenecks, evaluate tradeoffs, and guide hardware and system architecture decisions.
Responsibilities
- Develop system-level performance models for AI workloads and compute architectures
- Build simulation frameworks for AI models, software runtimes, and hardware systems
- Model compute units, memory hierarchies, and interconnects
- Incorporate software and runtime behavior into modeling frameworks
- Analyze system bottlenecks and evaluate architectural tradeoffs
- Guide microarchitectural and system-level design decisions
- Evaluate performance, latency, throughput, and energy efficiency
Requirements
- Strong background in computer architecture, system architecture, or performance modeling
- Experience building simulation or analytical models of complex hardware systems
- Strong programming skills in Python, C++, or similar languages
- Understanding of CPUs, GPUs, or AI accelerators
- Ability to analyze complex systems and identify performance bottlenecks
- Strong quantitative reasoning
Benefits
- Performance-based incentives
- Equity participation
- Medical coverage
- Dental coverage
- Vision coverage
- Paid time off
- Flexible work arrangements