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AI Systems Engineer, Hardware Architecture

Meta· Engineering
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Remote$260k - $319kFull-timePosted 2w ago

About the role

Principal-level AI Systems Engineer to define the hardware architecture strategy for next-generation AI-accelerated computing systems powering virtual and augmented reality products. Shapes silicon and systems roadmap for on-device AI inference and training across wearables, headsets, and spatial computing platforms, driving cross-functional alignment and architectural decisions.

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 networks to silicon microarchitecture
  • Establish technical direction for AI hardware platform decisions, including custom silicon vs. third-party IP evaluation and integration strategies
  • Partner with ML researchers and compiler teams to co-design hardware-software interfaces that maximize model efficiency on constrained wearable platforms
  • Represent hardware architecture in executive reviews, author architecture decision records and system specifications
  • Mentor and provide technical guidance to other engineers across hardware architecture and systems engineering
  • Evaluate emerging AI workloads, model architectures, and compute paradigms to inform future hardware platform investments

Qualifications

  • 15+ years of experience in hardware systems architecture, with a focus on AI, ML, or high-performance compute systems
  • Experience defining SoC or system-level architecture for AI inference or training workloads, including memory subsystem design, compute hierarchy, and interconnect topology
  • Experience with hardware-software co-design methodologies for on-device AI workloads, including familiarity with ML compiler stacks, operator fusion, and quantization impacts on hardware design
  • Experience developing system performance models and using simulation or analytical frameworks to evaluate architectural trade-offs at scale
  • Track record of driving multi-year hardware architecture roadmaps and influencing silicon strategy across large engineering organizations

Skills

Required:Hardware systems architectureHardware-software co-designSystem performance modelingRoadmapping and influenceCross-functional collaboration

Benefits

  • Benefits information referenced in the job posting (explicit benefits not listed in the excerpt)
Last updated Oct 23, 2026. Interested? Apply on the company site.

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