Low power AI/ML System Architect

Qualcomm • San Diego, CA

8d • $155,400 - $233,200

About The Position

As part of Qualcomm’s Low-Power AI (LPAI) Systems group, this role focuses on performance optimization, data-path and power analysis, and architecture of embedded AI subsystems, with emphasis on XR and ambient use cases. The engineer will drive power-efficient system design and analysis across DSP/AI subsystems by analyzing power-performance trade-offs and enabling optimizations across software and hardware for on-device AI.

Requirements

• Experience with embedded ML accelerators, NPUs, and processors, including understanding of low-power design principles and constraints.
• Experience working with embedded platforms, RTOS, and performance/power profiling tools for analysis, modeling, and automation.
• Strong programming skills in Python, PyTorch, and ExecuTorch.
• Solid understanding of memory systems, data movement, bandwidth analysis, and cache memory strategies.
• Strong fundamentals in power modeling, power analysis, and system-level power optimization.
• Hands-on experience with power measurement tools and data analysis techniques.
• Knowledge of fixed-point implementation and algorithm optimization techniques.
• Ability to work across cross-functional and geographically distributed teams.
• Bachelor's degree in Engineering, Information Systems, Computer Science, or a related field and 4+ years of Systems Engineering or related work experience; or a master's degree in one of these fields and 3+ years of related experience; or a PhD in one of these fields and 2+ years of related experience.

Nice To Haves

• Experience with Qualcomm NPU and LPAI architectures and SDKs.
• Exposure to ML model training and inference workloads and their power-performance characteristics.

Responsibilities

• Analyze and optimize performance and power of AI systems, with a focus on always-on AI workloads on Snapdragon SoCs.
• Support system integration, benchmarking, and commercialization of AI solutions across Mobile, XR, Compute, and IoT platforms.
• Perform detailed data-path and memory-access analysis, including cache, SRAM, and DDR, to identify bottlenecks affecting performance efficiency.

Benefits

• Competitive annual discretionary bonus program.
• Opportunity for annual RSU grants, except for employees on sales-incentive plans.
• Competitive benefits package designed to support employees at work, at home, and at play.

What This Job Offers

• Job Type: Full-time
• Career Level: Mid Level