AI Systems Engineer, Hardware Architecture

Meta; Madison (WI); On-site; USD 260,000 - 319,000; 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 AR/VR devices. You will shape silicon and system roadmaps for on‑device AI inference and training across wearables, headsets, and spatial platforms.

You will lead multi‑disciplinary teams, develop architectural models and simulators, evaluate bottlenecks, and drive decisions on custom silicon versus third‑party IP,

Qualifications

• 15+ years of experience in hardware systems architecture, with a focus on AI, ML, or high-performance compute systems.
• Experience defining SoC or system-level architecture for AI inference or training workloads, including memory subsystem design, compute hierarchy, and interconnect topology.
• Experience with hardware-software co-design methodologies for on-device AI workloads, including familiarity with ML compiler stacks, operator fusion, and quantization impacts on hardware design.
• 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 and influencing silicon strategy across large engineering organizations.

Responsibilities

• Define and own the multi-year architectural roadmap for AI compute subsystems across Meta's hardware product lines, including wearables and spatial computing devices
• Lead system-level architecture exploration for AI inference and training accelerators, including memory hierarchy design, interconnect topology, and power-performance-area tradeoffs
• Drive cross-functional alignment across silicon engineering, firmware, software, and product teams to translate AI workload requirements into hardware specifications
• Develop and maintain architectural models, performance simulators, and analytical frameworks to evaluate design tradeoffs at the system level
• Identify and resolve architectural bottlenecks across the AI compute stack, from neural network operators to silicon microarchitecture
• Establish technical direction for AI hardware platform decisions, including custom silicon versus third-party IP evaluation and integration strategies
• Partner with machine learning researchers and compiler teams to co-design hardware-software interfaces that maximize AI model efficiency on constrained wearable platforms
• Represent hardware architecture in executive-level technical reviews, authoring detailed architecture decision records and system specifications
• Mentor and provide technical guidance to other engineers across hardware architecture and systems engineering disciplines
• Evaluate emerging AI workloads, model architectures, and compute paradigms to proactively inform future hardware platform investments

Skills

Hardware systems architecture

Cross-functional collaboration

System performance modeling

Executive communication

Mentoring

Problem solving

Tools

ML compiler stacks

Performance simulators

System modeling tools

RTL handoff

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. You will drive architectural decisions that span custom silicon, memory subsystems, interconnects, 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 and own the multi-year architectural roadmap for AI compute subsystems across Meta's hardware product lines, including wearables and spatial computing devices

2. Lead system-level architecture exploration for AI inference and training accelerators, including memory hierarchy design, interconnect topology, and power-performance-area tradeoffs

3. Drive cross-functional alignment across silicon engineering, firmware, software, and product teams to translate AI workload requirements into hardware specifications

4. Develop and maintain architectural models, performance simulators, and analytical frameworks to evaluate design tradeoffs at the system level

5. Identify and resolve architectural bottlenecks across the AI compute stack, from neural network operators to silicon microarchitecture

6. Establish technical direction for AI hardware platform decisions, including custom silicon versus third-party IP evaluation and integration strategies

7. Partner with machine learning researchers and compiler teams to co-design hardware-software interfaces that maximize AI model efficiency on constrained wearable platforms

8. Represent hardware architecture in executive-level technical reviews, authoring detailed architecture decision records and system specifications

9. Mentor and provide technical guidance to other engineers across hardware architecture and systems engineering disciplines

10. Evaluate emerging AI workloads, model architectures, and compute paradigms to proactively inform future hardware platform investments

Minimum Qualifications:

Minimum Qualifications:

1. 15+ years of experience in hardware systems architecture, with a focus on AI, ML, or high-performance compute systems

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

3. Experience with hardware-software co-design methodologies for on-device AI workloads, including familiarity with ML compiler stacks, operator fusion, and quantization impacts on hardware design

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

5. Track record of driving multi-year hardware architecture roadmaps and influencing silicon strategy across large engineering organizations

Preferred Qualifications:

Preferred Qualifications:

1. Familiarity with custom silicon development flows, including architecture-to-RTL handoff, physical design constraints, and post-silicon validation feedback loops

2. Experience architecting AI systems for power- and area-constrained wearable or mobile devices, including VR headsets, AR glasses, or similar spatial computing platforms

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

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

Public Compensation:

$260,000/year to $319,000/year + bonus + equity + benefits

Industry: Internet

Equal Opportunity:

Meta is proud to be an Equal Employment Opportunity and Afficial 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].