Edge AI Software Engineer - Core Tools & GenAI

Qualcomm

San Diego (CA)

On-site

USD 141,000 - 211,000

Full time

14 days+

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Benefits offered by this job

Yearly bonus
RSU grants
Comprehensive benefits

Job summary

Qualcomm Technologies, Inc. is seeking an AI Software Core Engineer to develop and optimize ML software for the Qualcomm AI Stack across QAIRT, Genie, and related SDKs on Snapdragon platforms.

You will help build in-house tools, profile performance and memory, and advance edge-AI capabilities on embedded SoCs. The role emphasizes collaboration across cross-functional teams, robust software toolchains, and a culture of technical excellence with opportunities to contribute to AI runtime ecosystems

Qualifications

  • Bachelor’s, Master’s or PhD in a related field with strong software/embedded focus.
  • Experience in hardware/software integration and performance profiling.
  • Proficiency with C/C++/Python, LLVM/GNU toolchains, and build systems.

Responsibilities

  • Develop in-house software tools for the Qualcomm AI Stack SDKs (QAIRT/Genie).
  • Perform system-level performance and memory profiling on SoCs.
  • Analyze and optimize ML software for edge AI use cases.
  • Collaborate across teams; participate in code reviews.
  • Debug complex issues and ensure system reliability.
  • Contribute to toolchains and documentation.

Skills

C/C++/Python
Git
Embedded software
OS knowledge
Communication

Education

Bachelor's degree in CS/Engineering
Master's degree in CS/Engineering/IS
PhD in CS/Engineering/IS

Tools

LLVM
GNU toolchains
Make/CMake
Genie/QAIRT tools

Job description

Qualcomm Technologies, Inc. is seeking an AI Software Core Engineer to develop and optimize ML software for the Qualcomm AI Stack across QAIRT, Genie, and related SDKs on Snapdragon platforms.

You will help build in-house tools, profile performance and memory, and advance edge-AI capabilities on embedded SoCs. The role emphasizes collaboration across cross-functional teams, robust software toolchains, and a culture of technical excellence with opportunities to contribute to AI runtime ecosystems

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