SoC Performance Architect for AI Wearables

Meta

Sunnyvale (CA)

On-site

USD 180,000 - 240,000

Full time

14 days+

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Job summary

Meta Reality Labs is seeking an experienced Architect for the SoC Performance team in Sunnyvale, CA. You will lead performance modeling, workload profiling, and analysis to guide next-generation AI-enabled wearables.

The role requires deep expertise in SoC architecture, NoCs, memory subsystems, QoS, and HW-SW co-design, with strong scripting in Python. You will work across disciplines with vendors and internal teams to develop accurate models, run experiments, and communicate complex results

Qualifications

  • 8+ years of experience creating performance models using C/C++ or SystemC.
  • Experience with SoC architecture, NoCs, memory sub-system, QoS, and heterogeneous compute principles.
  • Proficiency in Python for automation and data visualization.
  • Experience with cycle-accurate performance models and HW-SW co-design.

Responsibilities

  • Conduct bottleneck analysis of existing and future SoCs to identify optimization opportunities.
  • Develop accurate models of IP components, SoC fabric, and DRAM to inform design decisions.
  • Analyze system workloads and create micro-benchmarks to evaluate performance.
  • Collaborate with hardware teams to optimize HW-SW co-design and drive measurable improvements.

Skills

Performance modeling
C/C++
SystemC
Python
SoC architecture
NoCs
QoS
Hardware-software co-design
Data analysis
RTL design verification

Education

Bachelor's or MS in EE/CS

Job description

Meta Reality Labs is seeking an experienced Architect for the SoC Performance team in Sunnyvale, CA. You will lead performance modeling, workload profiling, and analysis to guide next-generation AI-enabled wearables.

The role requires deep expertise in SoC architecture, NoCs, memory subsystems, QoS, and HW-SW co-design, with strong scripting in Python. You will work across disciplines with vendors and internal teams to develop accurate models, run experiments, and communicate complex results

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