AR/VR AI Hardware Architect: Imaging & On-Device AI

Meta; Bismarck (ND); On-site; USD 208,000 - 289,000; Full time

Job summary

Meta Reality Labs is seeking a principal-level AI Systems Engineer to define hardware architecture strategy for next-generation AI-accelerated computing powering VR/AR wearables and spatial computing platforms.

You will shape the silicon and systems roadmap for on-device AI inference/training, drive imaging pipeline architecture, and guide hardware-software co-design across silicon, firmware, camera systems, and ML platforms.

Qualifications

• 12+ years of experience in hardware systems architecture with focus on AI, ML, imaging, or high-performance compute systems.
• Deep expertise in camera pipeline architecture including ISP, sensor integration, and end-to-end imaging system design.
• Experience defining SoC or system-level architecture for AI inference or training workloads, including memory subsystem design, compute hierarchy, and interconnect topology.
• Experience architecting imaging subsystems for real-time computer vision applications, including multi-camera systems, depth sensing, and visual-inertial odometry.
• Experience with hardware-software co-design methodologies for on-device AI and imaging workloads, including familiarity with ML compiler stacks and ISP tuning workflows.
• Experience developing system performance models and evaluating architectural trade-offs at scale.
• Track record of driving multi-year hardware architecture roadmaps for imaging and AI systems and influencing silicon strategy across large engineering organizations.

Responsibilities

• Define multi-generation hardware architecture strategy for AI inference and training across VR, AR, and wearable device platforms.
• Lead system-level architectural exploration and trade-off analysis across compute, memory hierarchy, interconnect fabric, and power delivery for on-device AI workloads.
• Architect end-to-end camera and imaging pipelines, including sensor interfaces, ISP integration, and real-time image processing for CV and perception applications.
• Drive hardware-software co-design initiatives by partnering with silicon, firmware, camera systems, and ML platform teams to optimize AI and imaging pipeline performance.
• Define architectural requirements for camera subsystems including multi-camera synchronization, depth sensing, and low-latency visual processing for AR/VR.
• Establish architectural requirements and performance targets for custom AI accelerators, ISPs, SoCs, and subsystems in spatial computing devices.
• Develop and maintain system performance models and simulation frameworks to evaluate architectural decisions against real-world AI and imaging workloads.
• Provide architectural guidance and technical direction across hardware engineering organizations, aligning imaging and AI roadmaps with product and research priorities.
• Identify and resolve system-level bottlenecks in imaging latency, AI inference throughput, and energy efficiency for wearable/headset form factors.
• Engage with external silicon partners, camera vendors, and research institutions to evaluate emerging imaging technologies and incorporate into long-range architecture plans.
• Communicate architectural vision and rationale to executive leadership and cross-functional stakeholders through proposals and design reviews.

Skills

On-device AI

Camera pipelines

Hardware architecture

ML compiler stacks

System performance modeling

Hardware-software co-design

Image signal processing (ISP)

End-to-end imaging systems

Executive communication

Tools

RTL design

Simulation frameworks

Camera module integration

ISP tooling

Job description

Meta Reality Labs is seeking a principal-level AI Systems Engineer to define hardware architecture strategy for next-generation AI-accelerated computing powering VR/AR wearables and spatial computing platforms.

You will shape the silicon and systems roadmap for on-device AI inference/training, drive imaging pipeline architecture, and guide hardware-software co-design across silicon, firmware, camera systems, and ML platforms.