Responsibilities
- Define and drive SoC-level architecture for AR or AI wearable chips, including compute subsystems, memory hierarchy, interconnect topology, and power delivery strategies
- Lead architectural exploration and trade-off analysis across heterogeneous compute blocks, including CPU, GPU, vision, audio, and ML accelerators
- Collaborate with algorithms, firmware, and software teams to drive hardware-software co-design decisions
- Partner with IP vendors, power and performance architects, IP architects, and internal design teams to evaluate and integrate third-party and custom IP blocks into the SoC architecture
- Develop architectural specifications, interface definitions, and design guidelines that guide RTL implementation and physical design teams
- Provide architectural leadership and technical direction to other engineers across silicon, systems, and platform teams working on wearable device programs
- Contribute to long-term silicon roadmap planning by evaluating emerging process technologies, memory technologies, and compute paradigms relevant to AR/VR applications
Minimum Qualifications
- Bachelor's degree in Computer Science, Computer Engineering, relevant technical field, or equivalent practical experience
- 8+ years of experience in SoC architecture, microarchitecture definition, or system-level hardware design for consumer electronics or mobile/wearable platforms
- Experience architecting heterogeneous SoCs, encompassing CPU, GPU, neural processing, and hardware accelerator subsystems
- Expertise with high-speed I/O interfaces such as PCIe, USB, and LPDDR
- Experience with memory subsystem architecture, including cache hierarchy design, DRAM interface optimization, and on-chip interconnect (NoC) design
- Experience collaborating across hardware, firmware, and software disciplines to drive hardware-software co-design for real-time or latency-constrained workloads
Preferred Qualifications
- Experience architecting silicon for AR, VR, or wearable devices with stringent power and thermal constraints
- Experience with AI/ML accelerator architecture and optimizing memory hierarchy for neural network workloads for on-device inference
- Familiarity with advanced process node design considerations (e.g., 5nm and below) and their implications for SoC architecture decisions
- Experience with system MMUs and hardware security
$178,000/year to $250,000/year + bonus + equity + benefits
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