Hardware Systems Architect

Summary

As a Hardware Systems Architect at Reality Labs, you will lead architecture on upcoming AR/VR/Wearables products, help drive the overall strategy & roadmap, and be a part of the teams designing, building, and testing prototypes for future consumer AR/VR/Wearables reality experiences. We want people who work well in teams, can brainstorm big ideas, work in new technology areas, thrive in ambiguity, are able to map tradespaces, are able to drive a concept into a prototype, and can envision how a prototype could transition into a high-volume consumer product.The Reality Labs Hardware Systems Architect will lead the definition and convergence of complex and novel sub-systems, and product architectures aimed at pushing beyond the state-of-the-art consumer AR/VR/Wearable systems. These can span new sensing systems, display/optics systems, input devices, and full VR headsets. The role requires expert technical communication with cross-functional teams across ID, hardware engineering, partnerships, supply chain and core technology groups to drive incubation of new technologies from proof of concept through integration into products for mass production. This role requires excellent technical understanding of consumer electronics and AR/VR/Wearable reality systems across the stack.Starting with a broad engineering background in electrical engineering, computer science, semiconductors or related fields, we're looking for a unique system designer or architect. The ideal candidate would have strong systems skills, previous roles driving architecture convergence on complex consumer electronics products, and experience with SoC evaluation, optical systems, sensors, CV algorithms, software, and be able to work collaboratively with experts in different fields to make architectural trade-offs. In addition, this role requires past experience architecting systems to run ML workloads - assessing and selecting appropriate ML compute cores and driving system-level optimization of performance, power, latency and memory usage.

Required Skills

Hardware Systems Architect Responsibilities:

• Own system architectures encompassing compute, displays/optics, EE, sensors, calibration, and firmware from initial conception through prototyping, product development, and production ramp
• Across a portfolio of products, work with ML scientists and SW engineering teams to understand requirements for ML workloads that need to be supported. Drive selection/definition of compute silicon that has appropriate HW accelerators/cores for these workloads
• Lead product architecture for roadmap products, communicate trade-offs, program concerns and technical direction with specific focus on enabling ML-assisted augmented/virtual reality experiences
• Drive the technical scoping and development of new technologies to deliver generation-defining user experiences for future products on the roadmap
• Conduct detailed analysis and trade-off studies for complex systems
• Engage with technology project leads, and various component SMEs in creating the overall system architecture and platform as the starting point for product execution
• Deliver engineering solutions for the most challenging architectural problems in early phase concept development (ensuring translation of marketing requirements to product)
• Communicate technology and product strategy effectively to both internal and external stakeholders
• Partner with management and cross functional teams on long term technology investments
• Create proof-of-concept physical prototypes
• Collaborate with cross-functional teams on blank-slate and early-phase prototyping and product exploration, mapping it to strategic and product questions which need to be resolved
• Create hardware system metrics, KPIs, standards and tools
• Travel up to 15% time domestically and internationally

Minimum Qualification

Minimum Qualifications:

• 7+ years of product experience in electrical, systems or computer engineering
• BS in Electrical Engineering, Computer Engineering other related technical field or equivalent industry experience
• Experience with architecture and systems engineering across electrical, firmware, audio and optical systems
• Hands-on experience with: on-device machine learning frameworks (e.g. TensorFlow, PyTorch etc.), popular NNs and corresponding implementations on relevant hardware, architecture and specifications of compute blocks that are designed to run these models, methodologies for benchmarking compute/memory usage/power consumption and latency on platforms running ML workloads
• Experience with mainstream silicon IPs and SDKs for on-device machine learning, e.g. ARM Mali GPUs, Ethos NPUs, Cadence G/HIFI DSPs, Qualcomm Hexagon MPUs
• Experience integrating and delivering one or more of these technologies: displays, silicon, sensors
• Experience in rapid prototyping and creating proof of concept models to share ideas and improve architectural decisions
• Communication experience working with Product Development engineers, Product Managers and other hardware/software cross-functional teams
• Experience working with partnerships teams and external partners at both a supply base and product level

Preferred Qualification

Preferred Qualifications:

• MS/PhD in Electrical Engineering, Computer Engineering other related technical field or equivalent experience
• Experience in firmware development, programming, computer vision, OS, game development, and complex sensing systems
• Experience modeling system power and, using those models, inform trade-offs against key architectural decisions (e.g. battery life, thermals, silicon roadmaps, power load profiles)
• Understanding of memory subsystems including mass storage and filesystem as well as volatile memory and memory management and their impacts on overall system performance
• Experience with AR/VR or systems aimed at capturing/processing/delivering audio visual, IMU or other positional data streams
• Experience creating system models to analyze system compute, latency and communication interface bandwidths across multiple subsystems within a heterogeneous compute environment in order to define the system architecture to meet the overall goals of the product definition
• Experience with influencing silicon vendors roadmaps and SOC features sets with emphasis on using advanced IP in the realms of Machine Learning, Graphics and Imaging

EOE

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.

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