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Open nowFirst seen 9 hours ago

AI Systems Engineer, Hardware Architecture

Meta1,234 open roles

Where
Remote, US; New York, NY
Work mode
Remote
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Your applicationOpen nowAI Systems Engineer, Hardware ArchitectureMeta · Remote, US; New York, NY

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The clock on this job

Early applications get read.

12.1% of postings close within 7 days. Measured by our own scanner across the market. Meta postings stay open a median of 35 days.

Share of postings closed within
  1. 2.1%1 day
  2. 4.5%3 days
  3. 12.1%7 days
  4. 19.1%14 days
  5. 35.6%30 days
  6. 52.7%60 days
This job: first seen 9 hours ago

Meta median: 35 days open

The posting

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 virtual and augmented reality products. In this role, you will shape the long-term silicon and systems roadmap for on-device AI inference and training workloads across wearables, headsets, and spatial computing platforms. A core focus of this role is driving the architecture of advanced imaging systems and camera pipelines that enable real-time perception, scene understanding, and mixed reality experiences. You will drive architectural decisions that span custom silicon, memory subsystems, interconnects, image signal processors (ISPs), camera subsystems, and software-hardware co-design, ensuring Meta's AI hardware remains at the forefront of performance, efficiency, and capability for immersive computing experiences.

Responsibilities

  • Define multi-generation hardware architecture strategy for AI inference and training systems 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 computer vision and perception applications
  • Drive hardware-software co-design initiatives by partnering with silicon engineering, firmware, camera systems, and ML platform teams to optimize end-to-end 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 applications
  • Establish architectural requirements and performance targets for custom AI accelerators, ISPs, SoCs, and supporting subsystems in spatial computing devices
  • Develop and maintain system performance models and simulation frameworks to evaluate architectural decisions against real-world AI and imaging workload characteristics
  • 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 and headset form factors
  • Engage with external silicon partners, camera module vendors, and research institutions to evaluate emerging imaging technologies and incorporate them into long-range architecture plans
  • Communicate architectural vision and technical rationale to executive leadership and cross-functional stakeholders through written proposals and design reviews

Minimum Qualifications

  • 12+ years of experience in hardware systems architecture, with a focus on AI, ML, imaging systems, or high-performance compute systems
  • Deep expertise in camera pipeline architecture, including image signal processing (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 using simulation or analytical frameworks to evaluate 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

Preferred Qualifications

  • Familiarity with custom silicon development flows for imaging and AI accelerators, including architecture-to-RTL handoff, physical design constraints, and post-silicon validation
  • Experience architecting AI and imaging systems for power- and area-constrained wearable or mobile devices, including VR headsets, AR glasses, or similar spatial computing platforms
  • Expertise in computational photography pipelines, HDR processing, and neural ISP architectures
  • Background in collaborating with ML research and camera teams to translate novel imaging algorithms and model architectures into hardware-efficient deployment targets
  • Experience evaluating and integrating emerging memory technologies (e.g., HBM, LPDDR5X, in-memory compute) into AI and imaging system architectures

US: $208,000/year to $289,000/year + bonus + equity

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