Remote AI Systems Architect — On-Device AI Hardware

Meta; Northern (KY); Remote; USD 180,000 - 280,000; Full time

Job summary

Meta Reality Labs is seeking a principal-level AI Systems Engineer to define the hardware architecture strategy for next-generation AI-accelerated computing systems powering virtual and augmented reality products. You will shape the long-term silicon and systems roadmap for on-device AI inference and training workloads across wearables, headsets, and spatial computing platforms.

You will drive architectural decisions and collaborate across silicon, firmware, software, and ML researchers to

Responsibilities

• Define and own the multi-year architectural roadmap for AI compute subsystems across Meta's hardware product lines, including wearables and spatial computing devices
• Lead system-level architecture exploration for AI inference and training accelerators, including memory hierarchy design, interconnect topology, and power-performance-area tradeoffs
• Drive cross-functional alignment across silicon engineering, firmware, software, and product teams to translate AI workload requirements into hardware specifications
• Develop and maintain architectural models, performance simulators, and analytical frameworks to evaluate design tradeoffs at the system level
• Identify and resolve architectural bottlenecks across the AI compute stack, from neural network operators to silicon microarchitecture
• Establish technical direction for AI hardware platform decisions, including custom silicon versus third-party IP evaluation and integration strategies
• Partner with machine learning researchers and compiler teams to co-design hardware-software interfaces that maximize AI model efficiency on constrained wearable platforms

Job description

Meta Reality Labs is seeking a principal-level AI Systems Engineer to define the hardware architecture strategy for next-generation AI-accelerated computing systems powering virtual and augmented reality products. You will shape the long-term silicon and systems roadmap for on-device AI inference and training workloads across wearables, headsets, and spatial computing platforms.

You will drive architectural decisions and collaborate across silicon, firmware, software, and ML researchers to