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# Performance Modeling Architect - AI Systems

- **Company:** Auradine, Inc.
- **Location:** Austin, NC, United States
- **Salary:** $200,000.0 - $300,000.0
- **Contract:** Permanent contract
- **Skills:** Artificial Intelligence, C++ (Programming Language), Computer Programming, Microprocessors, Python (Programming Language), Machine Learning, Systems Architecture, System on a Chip, Graphics Processing Unit (GPU), Information Technology, Low Latency, Modeling and Simulation, Machine Learning Operations
- **Published:** October 27, 2026
- **Apply:** https://www.careerbuilder.com/job-details/performance-modeling-architect-ai-systems-austin-tx--dd15a505-3cbd-4c78-9911-a5979e8690f7

## About the Role

Artificial Intelligence (AI), Performance Modeling, System Architecture, Energy Efficiency, Hardware Architecture, Architectural Services, Computer Systems, Artificial Intelligence (AI), Simulation, System-on-a-Chip (SoC), Strong background in computer architecture, system architecture, or performance modeling.

Experience building simulation or analytical models of complex hardware systems.

Strong programming skills (Python, C++, or similar) for modeling and simulation frameworks.

Understanding of modern compute architectures such as CPUs, GPUs, or AI accelerators.

Ability to analyze complex systems and identify performance bottlenecks.

Strong quantitative reasoning and ability to translate models into architecturalinsights.

Preferred Qualifications

Experience modeling AI workloads or machine learning systems.

Familiarity with architectural simulators or performance modeling tools.

Experience with memory systems, interconnect architectures, or accelerator design.

Exposure to hardware-software co-design methodologies., Experience modeling performance across multiple layers of the stack, including software runtimes and hardware platforms.

## Description

Develop system-level performance models for AI workloads and compute architectures.

Build simulation frameworks that capture interactions between AI models, software runtimes, and hardware systems.

Model key components of SoC architecture including compute units, memory hierarchies, and interconnects.

Incorporate relevant software and runtime behavior into modeling frameworks to reflect realistic system execution.

Analyze system bottlenecks and evaluate architectural tradeoffs across the platform.

Work closely with hardware architects to guide microarchitectural and system-level design decisions.

Collaborate with software and ML teams to incorporate realistic workloads into modeling frameworks.

Use modeling and simulation to evaluate performance, latency, throughput, and energy efficiency across target applications.