Senior AI Systems Architect - On-Device Compute for Wearables

Meta; Phoenix (AZ); On-site; USD 260,000 - 319,000; 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 on-device AI inference and training for wearables and spatial computing platforms.

You will shape silicon and software-hardware co-design, lead architecture exploration, and drive technical direction across product teams to maximize performance, efficiency, and capability.

Qualifications

• 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.
• Represent hardware architecture in executive-level technical reviews, authoring detailed architecture decision records and system specifications.
• Mentor and provide technical guidance to other engineers across hardware architecture and systems engineering disciplines.
• Evaluate emerging AI workloads, model architectures, and compute paradigms to proactively inform future hardware platform investments.

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.
• Represent hardware architecture in executive-level technical reviews, authoring detailed architecture decision records and system specifications.
• Mentor and provide technical guidance to other engineers across hardware architecture and systems engineering disciplines.
• Evaluate emerging AI workloads, model architectures, and compute paradigms to proactively inform future hardware platform investments.

Skills

Hardware architecture

AI compute workloads

System performance models

Cross-functional alignment

Memory hierarchy design

Tools

ML compiler stacks

Performance simulators

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 on-device AI inference and training for wearables and spatial computing platforms.

You will shape silicon and software-hardware co-design, lead architecture exploration, and drive technical direction across product teams to maximize performance, efficiency, and capability.