Job description

Meta is seeking highly skilled Design Engineers to join our team. In this role, you will contribute to the development of advanced technology solutions, including machine learning and network acceleration. You will collaborate with researchers and engineers to design, implement, and optimize low-power hardware accelerators, state-of-the-art SoCs, and custom silicon solutions that enable the next generation of innovative devices and hardware. Contribute to ASIC digital µArchitecture and design Assist performance/power analysis of the design and help meet power and performance targets Work with architects to map algorithms onto the hardware and specify requirements for IP and subsystems integration Collaborate with adjacent teams such as Verification, Physical Design, and Design-for-Test Develop micro-architecture, RTL coding, and design verification for complex IPs Drive IP/sub-system micro-architecture and RTL design in collaboration with DV and PD leads Bachelor's degree in Computer Science, Computer Engineering, relevant technical field, or equivalent practical experience 8+ years of experience as a Hardware Design Engineer for production silicon shipped in volume Experience in digital design µArchitecture, RTL coding, and micro-architecture development Experience communicating technical design decisions and trade-offs to cross-functional partners such as verification, physical design, and architecture teams Experience with interconnect configurator and generation flows, and technically leading or mentoring engineers across deliverables Experience collaborating with physical design and timing partners on interconnect implementation, including timing- and floorplan-aware microarchitecture, pipelining and repeater strategy, physical partitioning, clock- and power-domain crossings, and architecture versus physical implementation trade-offs to close frequency, area, and power targets Experience defining fabric architecture and microarchitecture, including topology, address mapping, ordering and coherency requirements, buffering, quality-of-service, arbitration, and virtual-channel schemes, with industry-standard interconnect and bus protocols, and performance modeling and traffic-driven latency and bandwidth budgeting correlated against RTL results Demonstrated experience developing interconnect/NoC/fabric IP from architecture specification through RTL delivery Demonstrated ability to integrate AI tools to optimize/redesign workflows and drive measurable impact (e.g., efficiency gains, quality improvements) Experience adhering to and implementing responsible, ethical AI practices (e.g., risk assessment, bias mitigation, quality and accuracy reviews) Demonstrated ongoing AI skill development (e.g., prompt/context engineering, agent orchestration) and staying current with emerging AI technologies

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Keywords to mirror

machine learningai

Platform: meta
Effort: medium