Lead AI & Imaging Hardware Architect for XR

Meta; Montpelier (VT); On-site; USD 208,000 - 289,000; 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 VR/AR wearables.

You will shape silicon and system roadmaps for on-device AI inference and training workloads, drive imaging pipelines, and collaborate across silicon, firmware, camera systems, and ML platforms to deliver high-performance, energy-efficient immersive experiences.

Qualifications

• 12+ years in hardware systems architecture with AI/imaging focus.
• Deep expertise in camera pipeline architecture and ISP.
• Experience defining SoC/system-level architecture for AI workloads.
• Experience imaging subsystems for real-time CV incl. multi-camera systems.
• Experience HW-SW co-design for on-device AI with ML compiler knowledge.
• Experience building system performance models and simulations.
• Track record guiding multi-year hardware roadmaps.

Responsibilities

• Define multi-generation hardware architecture strategy for AI inference and training on VR/AR wearables.
• Lead system-level exploration across compute, memory, interconnect, and power.
• Architect camera and imaging pipelines with sensor interfaces and ISP integration.
• Drive HW-SW co-design with silicon, firmware, and ML platform teams.
• Establish requirements for camera subsystems including multi-camera sync and depth sensing.
• Develop performance models to evaluate architectural decisions.

Skills

Hardware systems

AI/ML imaging

Camera pipeline

SoC architecture

HW-SW co-design

Performance modeling

Roadmap planning

Tools

ML compiler stacks

ISP tuning workflows

RTL handoff processes

Simulation frameworks

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 VR/AR wearables.

You will shape silicon and system roadmaps for on-device AI inference and training workloads, drive imaging pipelines, and collaborate across silicon, firmware, camera systems, and ML platforms to deliver high-performance, energy-efficient immersive experiences.