Lead AI Systems Architect for Mobile AI & Frameworks

Qualcomm; San Diego (CA); On-site; USD 217,000 - 325,000; Full time

Job summary

Qualcomm Technologies, Inc. is seeking a Principal-level System Lead in San Diego to drive AI-centric mobile system architectures. You will translate AI use cases into scalable, power-efficient system implementations leveraging Qualcomm’s mobile SoCs and software platforms.

The role emphasizes AI workloads, on-device inference, and collaboration with OEMs and cross-functional teams to optimize performance, latency, and energy efficiency.

Qualifications

• Bachelor's degree in Electrical Engineering, Computer Science, Computer Engineering, or related field with 8+ years of relevant experience.
• Master's degree in Electrical Engineering, Computer Science, Computer Engineering, or related field with 7+ years of relevant experience.
• PhD in Electrical Engineering, Computer Science, Computer Engineering, or related field with 6+ years of relevant experience.
• 8+ years of experience in semiconductor product development.
• 5+ years in a technical leadership role.

Responsibilities

• Product & System Architecture (AI Focus) for mobile AI workloads.
• Analyze OEM use cases involving generative AI, diffusion models, on-device inference, and camera-centric AI.
• Define architectural enhancements across accelerators, CPUs, GPUs, memory subsystems, and power management.
• Evaluate trade-offs among performance, power, memory bandwidth, latency, and thermal constraints.
• Collaborate with hardware, software, systems, and AI platform teams to align with roadmaps.

Skills

Technical leadership

Cross-functional collaboration

AI system architecture

Education

Bachelor's degree in EE/CS/CE

Master's degree in EE/CS/CE

PhD in EE/CS/CE

Job description

Qualcomm Technologies, Inc. is seeking a Principal-level System Lead in San Diego to drive AI-centric mobile system architectures. You will translate AI use cases into scalable, power-efficient system implementations leveraging Qualcomm’s mobile SoCs and software platforms.

The role emphasizes AI workloads, on-device inference, and collaboration with OEMs and cross-functional teams to optimize performance, latency, and energy efficiency.