AI Systems Engineer, Hardware Architecture

Meta; Denver (CO); 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 products. You will shape the silicon and systems roadmap for on‑device AI inference and training across wearables, headsets, and spatial platforms.

A core focus is driving the architecture of imaging systems and camera pipelines enabling real-time perception and mixed reality experiences.

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 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 and interconnect topology.
• Experience architecting imaging subsystems for real-time computer vision applications, including multi-camera systems and depth sensing.
• Experience with hardware-software co-design methodologies for on-device AI and imaging workloads, including ISP tuning workflows.
• Track record of driving multi-year hardware architecture roadmaps for imaging and AI systems.

Responsibilities

• Define multi-generation hardware architecture strategy for AI inference and training systems across VR, AR, and wearables.
• Lead system-level architectural exploration across compute, memory, interconnect and power delivery for on-device AI workloads.
• Architect end-to-end camera and imaging pipelines, including sensor interfaces and ISP integration.
• Drive hardware-software co-design initiatives with silicon, firmware, camera systems, and ML platform teams to optimize AI/imaging performance.
• Define architectural requirements for camera subsystems including multi-camera synchronization, depth sensing, and low-latency processing.
• Set targets for custom AI accelerators, ISPs, and SoCs in spatial computing devices.
• Develop and maintain system performance models to evaluate architectural decisions against AI/imaging workloads.
• Provide architectural guidance across hardware teams aligning imaging and AI roadmaps with product priorities.
• Identify and resolve system bottlenecks in imaging latency, AI throughput, and energy efficiency.
• Engage with external silicon partners and research institutions to evaluate emerging imaging technologies and integration plans.
• Communicate architectural vision to executive leadership and stakeholders.

Skills

Hardware architecture

AI inference workloads

Camera pipelines

Systems co-design

SoC architecture

Executive communication

Job description

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 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.

Required Skills:

AI Systems Engineer, Hardware Architecture Responsibilities:

1. Define multi-generation hardware architecture strategy for AI inference and training systems across VR, AR, and wearable device platforms

2. Lead system-level architectural exploration and trade-off analysis across compute, memory hierarchy, interconnect fabric, and power delivery for on-device AI workloads

3. Architect end-to-end camera and imaging pipelines, including sensor interfaces, ISP integration, and real-time image processing for computer vision and perception applications

4. 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

5. Define architectural requirements for camera subsystems including multi-camera synchronization, depth sensing, and low-latency visual processing for AR/VR applications

6. Establish architectural requirements and performance targets for custom AI accelerators, ISPs, SoCs, and supporting subsystems in spatial computing devices

7. Develop and maintain system performance models and simulation frameworks to evaluate architectural decisions against real-world AI and imaging workload characteristics

8. Provide architectural guidance and technical direction across hardware engineering organizations, aligning imaging and AI roadmaps with product and research priorities

9. Identify and resolve system-level bottlenecks in imaging latency, AI inference throughput, and energy efficiency for wearable and headset form factors

10. Engage with external silicon partners, camera module vendors, and research institutions to evaluate emerging imaging technologies and incorporate them into long-range architecture plans

11. Communicate architectural vision and technical rationale to executive leadership and cross-functional stakeholders through written proposals and design reviews

Minimum Qualifications:

Minimum Qualifications:

1. 12+ years of experience in hardware systems architecture, with a focus on AI, ML, imaging systems, or high-performance compute systems

2. Deep expertise in camera pipeline architecture, including image signal processing (ISP), sensor integration, and end-to-end imaging system design

3. Experience defining SoC or system-level architecture for AI inference or training workloads, including memory subsystem design, compute hierarchy, and interconnect topology

4. Experience architecting imaging subsystems for real-time computer vision applications, including multi-camera systems, depth sensing, and visual-inertial odometry

5. Experience with hardware-software co-design methodologies for on-device AI and imaging workloads, including familiarity with ML compiler stacks and ISP tuning workflows

6. Experience developing system performance models and using simulation or analytical frameworks to evaluate architectural trade-offs at scale

7. Track record of driving multi-year hardware architecture roadmaps for imaging and AI systems and influencing silicon strategy across large engineering organizations

Preferred Qualifications:

Preferred Qualifications:

1. Expertise in computational photography pipelines, HDR processing, and neural ISP architectures

2. 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

3. Experience evaluating and integrating emerging memory technologies (e.g., HBM, LPDDR5X, in-memory compute) into AI and imaging system architectures

4. Background in collaborating with ML research and camera teams to translate novel imaging algorithms and model architectures into hardware-efficient deployment targets

5. Familiarity with custom silicon development flows for imaging and AI accelerators, including architecture-to-RTL handoff, physical design constraints, and post-silicon validation

Public Compensation:

$208,000/year to $289,000/year + bonus + equity + benefits

Industry:

Internet

Equal Opportunity:

Meta is proud to be an Equal Employment Opportunity and affirmative Action employer. We do not discriminate based upon race, religion, color, national origin, sex (including pregnancy, childbirth, or related medical conditions), sexual orientation, gender, gender identity, gender expression, transgender status, sexual stereotypes, age, status as a protected veteran, status as an individual with a disability, or other applicable legally protected characteristics. We also consider qualified applicants with criminal histories, consistent with applicable federal, state and local law. Meta participates in the E-Verify program in certain locations, as required by law. Please note that Meta may leverage artificial intelligence and machine learning technologies in connection with applications for employment.

Meta is committed to providing reasonable accommodations for candidates with disabilities in our recruiting process. If you need any assistance or accommodations due to a disability, please let us know at [e-mail].