Low power AI/ML System Architect
Core
Architecting and optimizing low-power embedded AI subsystems for XR and ambient use cases, focusing on performance/power trade-offs across DSP/AI hardware and software.
Role type
Senior IC low-power AI/ML system architect
Builds
Power-efficient on-device AI solutions for Mobile, XR, Compute, and IoT platforms
Domain
Semiconductor / Embedded Systems / AI Hardware
Deliverable
production ML models
Required skills
Embedded ML accelerators, NPUs, low power design, RTOS, Python, PyTorch, Executorch, memory systems, data movement, bandwidth analysis, cache strategies, power modeling, power analysis, system-level power optimization, fixed-point implementation, algorithm optimization
Preferred skills
Qualcomm NPU and LPAI architectures, SDKs, ML model training and inference workloads
Technologies
Snapdragon SOCs, Python, PyTorch, Executorch
Responsibilities
Analyze and optimize performance and power of AI systems with focus on always-on AI workloads; Support system integration, benchmarking, and commercialization of AI solutions; Perform detailed data-path and memory-access analysis to identify bottlenecks
Seniority
Senior, hands-on IC
