AI Systems Engineer, Hardware Architecture

Job Title

AI Systems Engineer, Hardware Architecture

Role Summary

Principal-level hardware systems architect for Meta Reality Labs focused on defining multi-generation silicon and system architecture for on-device AI inference and training across VR, AR, and wearable platforms.

Main responsibilities include setting long-term architecture strategy for custom SoCs, AI accelerators, memory and interconnect subsystems, and end-to-end camera and imaging pipelines to support real-time perception and mixed-reality experiences.

Experience Level

Senior - principal-level; requires 12+ years of relevant hardware systems architecture experience.

Responsibilities

Design and lead system-level architecture workstreams for AI and imaging systems; drive cross-team architecture decisions and roadmaps.

• Define multi-generation hardware architecture strategy for on-device AI inference and training across VR/AR/wearable platforms.
• Lead architectural trade-off analyses across compute, memory hierarchy, interconnect fabric, and power delivery.
• Architect end-to-end camera and imaging pipelines including sensor interfaces and ISP integration.
• Drive hardware–software co-design with silicon, firmware, camera systems, and ML platform teams.
• Specify camera subsystem requirements: multi-camera sync, depth sensing, and low-latency visual processing.
• Set performance targets for custom AI accelerators, ISPs, SoCs, and supporting subsystems.
• Develop system performance models and simulation frameworks to evaluate architectural choices.
• Provide architectural guidance across hardware teams and communicate vision to leadership and stakeholders.
• Engage with external silicon partners, camera-module vendors, and research institutions to evaluate emerging imaging technologies.

Requirements

Concise list of required and preferred technical qualifications.

• Must-have: 12+ years of experience in hardware systems architecture focused on AI, ML, imaging systems, or high-performance compute.
• Must-have: Deep expertise in camera pipeline architecture, including image signal processing (ISP) and sensor integration.
• Must-have: Experience defining SoC or system-level architecture for AI inference or training workloads, including memory subsystem design and interconnect topology.
• Must-have: Experience architecting imaging subsystems for real-time computer vision (multi-camera systems, depth sensing, visual-inertial odometry).
• Must-have: Experience with hardware–software co-design for on-device AI and familiarity with ML compiler stacks and ISP tuning workflows.
• Must-have: Experience developing system performance models and using simulation or analytical frameworks to evaluate architectural trade-offs.
• Must-have: Proven track record driving multi-year hardware architecture roadmaps and influencing silicon strategy.
• Nice-to-have: Expertise in computational photography, HDR processing, and neural ISP architectures.
• Nice-to-have: Experience designing for power- and area-constrained wearable or mobile devices (VR headsets, AR glasses).
• Nice-to-have: Familiarity with emerging memory technologies (HBM, LPDDR5X, in-memory compute) and custom silicon development flows.
• Nice-to-have: Experience translating novel imaging algorithms and ML research into hardware-efficient implementations.

Education Requirements

Not specified.

About the Company

Company: Meta Platforms

Headquarters: Menlo Park, California, United States

American technology company that develops social networking products (Facebook, Instagram, WhatsApp) and invests in virtual/augmented reality hardware and software through Reality Labs, focusing on connectivity, advertising, and immersive computing experiences.