Senior Embedded ML Software Architect - Snapdragon Mobile

QUALCOMM, Inc.; San Diego (CA); On-site; USD 235,000 - 352,000; Full time

Job summary

Qualcomm Technologies, Inc. in San Diego seeks an experienced Embedded ML SW Architect focused on Snapdragon Mobile products.

You will design high level architectures for new use-cases and features, and drive performance and power optimizations across software, hardware stacks and ML tooling. As a senior member of the team, you will collaborate with development leads, software and hardware architects, project engineers, product managers, customers, OEMs and partners to deliver on-device AI

Qualifications

• Bachelor's degree in Computer Science, Engineering, Information Systems or related field with 8+ years of hardware/software/systems experience.
• Master's degree in relevant field with 7+ years of experience or PhD with 6+ years of experience.
• Strong programming skills in C, C++ and Python; knowledge of mobile platforms and AI frameworks like TensorFlow/PyTorch.

Responsibilities

• Develop architecture for complex features and experiences built around AI for Snapdragon Mobile products; propose enhancements.
• Research requirements and independently define solutions with cross-functional teams; prototype development.
• Architect on-device agentic experiences with memory management and heterogeneous compute across CPU/GPU/NPU under tight power/memory budgets.

Skills

C

C++

Python

Java

Kotlin

Typescript

Education

Bachelor's degree in CS/Engineering + 8+ years

Master's degree + 7+ years

PhD + 6+ years

Tools

TensorFlow

PyTorch

Job description

Qualcomm Technologies, Inc. in San Diego seeks an experienced Embedded ML SW Architect focused on Snapdragon Mobile products.

You will design high level architectures for new use-cases and features, and drive performance and power optimizations across software, hardware stacks and ML tooling. As a senior member of the team, you will collaborate with development leads, software and hardware architects, project engineers, product managers, customers, OEMs and partners to deliver on-device AI