Hardware Systems Architect, AI Hardware Products

Meta•Menlo Park, CA

1d•$208,000 - $289,000

About The Position

At Meta Superintelligence Labs, the Hardware Systems Architect leads architecture for upcoming consumer AI hardware products and helps define the overall strategy and roadmap. The role contributes to teams designing, building, and testing prototypes for future consumer AI experiences. It defines and converges complex, novel subsystems and product architectures aimed at advancing consumer AI systems, including sensing, display and optics systems, and input and output devices. The architect communicates with cross-functional teams spanning industrial design, hardware engineering, partnerships, supply chain, and core technology groups. The role drives the incubation of new technologies from proof of concept through integration into products for mass production. It calls for a broad engineering background, such as electrical engineering, mechanical engineering, computer science, or semiconductors, and a strong systems designer or architect.

Requirements

B.S. in Electrical Engineering, Computer Engineering, or another related technical field, with product experience in electrical, systems, or computer engineering.
12+ years of experience in architecture definition and/or systems engineering in one or more of these areas: electrical, silicon, firmware, audio, sensors, wireless connectivity, displays, or optical systems.
Knowledge of computer architecture fundamentals.
Experience with rapid prototyping and creating proof-of-concept models to communicate ideas and improve architectural decisions.
Experience communicating with product development engineers, product managers, and other hardware and software cross-functional teams.
Experience working with partnership teams and external partners at both supply-base and product levels.
Experience working in cross-functional teams, navigating ambiguity, mapping trade spaces, and transitioning concepts from prototype to high-volume consumer products.
Systems-level engineering experience, including experience with areas such as SoC evaluation, optical systems, sensors, computer vision algorithms, software, or AI.
Experience with consumer electronics systems spanning hardware, firmware, and software integration.

Nice To Haves

Experience modeling system power and using models to inform trade-offs in architectural decisions such as battery life, thermals, silicon roadmaps, and power load profiles.
Demonstrated ability to integrate AI tools to optimize or redesign workflows and drive measurable impact, such as efficiency gains or quality improvements.
Experience creating system models to analyze compute, latency, and communication-interface bandwidth across multiple subsystems in heterogeneous compute environments to define product system architecture.
M.S. or Ph.D. in Electrical Engineering, Computer Engineering, or another related technical field, or equivalent industry experience.
Understanding of memory subsystems, including mass storage and filesystems, volatile memory, memory management, and their impact on overall system performance.
Demonstrated ongoing AI skill development, such as prompt or context engineering and agent orchestration, and keeping current with emerging AI technologies.
Experience with AI systems aimed at capturing, processing, or delivering audio-visual, IMU, or other positional data streams.
Experience adhering to and implementing responsible, ethical AI practices, such as risk assessment, bias mitigation, and quality and accuracy reviews.
Experience in one or more of these areas: firmware development, programming, computer vision, Android or Zephyr OS, game development, and complex sensing systems.

Responsibilities

Own platform system architecture definition across one or more subsystems—including compute and memory, displays and optics, electrical engineering, sensors, audio, wireless connectivity, I/O, and firmware—from conception through prototyping, product development, and production ramp.
Work across a portfolio of products with system architects and software engineering teams to understand and document workload requirements, supporting selection and definition of compute silicon with appropriate hardware accelerators and cores.
Maintain detailed workload specifications and assumptions to ensure common understanding and alignment across teams implementing new features.
Profile workloads to understand system resource utilization metrics for existing and new software features on target compute platforms.
Conduct detailed analyses and trade-off studies to inform architecture decisions.
Deliver engineering solutions to high-impact architectural problems during early concept development, translating marketing requirements into products.
Communicate technology and product strategy to internal and external stakeholders.
Guide management and partner teams on long-term technology investments.
Create hardware system metrics, standards, and tools.
Drive development of system requirements for new AR and/or AI experiences and help advance technology and research roadmaps.
Travel up to 20% domestically and internationally.