About The Position

As a leading technology innovator, Qualcomm pushes the boundaries of what's possible to enable next-generation experiences and drive digital transformation, creating a smarter, connected future for all. As an AI Software Core Software Engineer, you will develop and implement cutting-edge machine learning techniques that enable the efficient utilization of state-of-the-art solutions across various technology verticals. In this role, you will be responsible for developing tools and supporting AI SW platform for the Qualcomm AI Stack spanning the Qualcomm AI Runtime (QAIRT) SDK, specifically Core software including Generative AI Inference Extensions (Genie) and the corresponding HW ML accelerator back-end support on the SoC. You will be responsible for researching state-of-the art AI toolchains, performance / memory and HW (CPU/NPU/eNPU) profiling for Edge-AI use cases on the embedded SoC. You will have the opportunity to demonstrate your passion for software tools (developed in house and/or bring in off-the-shelf AI tools), support AI SW ecosystem across development and test and customer support. You will contribute to software toolchains and system level performance / memory profiling across a wide variety of OSes and platforms. You will collaborate with cross-functional teams to deliver robust, scalable AI software solutions, and contribute to a culture of technical excellence, knowledge sharing, and continuous improvement within the AI Software team.

Requirements

  • Bachelor’s degree in Engineering, Information Systems, Computer Science, or related field.
  • Proficiency in software tools development using C/C++/Python, compiler toolchains
  • Projects or Internships experience (Entry level) / 2+ years (Senior) of general software development experience.
  • Excellent communication skills (verbal, presentation, and writing).

Nice To Haves

  • Master’s degree in Computer Science, Computer Engineering, or Electrical Engineering.
  • 1+ years of experience building embedded software applications.
  • Experience in using and developing AI solutions in one or more of these frameworks: Tensorflow, JAX, TFLite, LiteRT, PyTorch, ExecuTorch, ONNX Runtime
  • Familiarity with various generative AI model architectures such as LLMs.
  • Strong understanding of hardware acceleration and deployment of generative AI inference at the connected edge.
  • Experience with development in different OS/platforms like Android, Linux, Windows
  • Knowledge of low-level interactions between operating systems (e.g., Linux, Android, Windows, QNX, etc.) and hardware.
  • Experience with CMake-based build environments.
  • Experience using/integrating Qualcomm AI Stack products (e.g., QNN, Genie).
  • Experience with agile software development practices and git-based SCM.
  • Ability to collaborate across a globally diverse team and manage multiple interests.

Responsibilities

  • You will be involved in developing in-house software tools or research off-the-shelf 3rd party toolchains, compilers required for the Qualcomm AI Stack SDKs, specifically QAIRT and Genie, to support the execution of the latest generative AI models on Snapdragon platforms for various AI use cases across a wide-variety of SoCs and OS platforms (Android, Linux, QNX, Windows, Zephyr, etc.)
  • You will be involved in System level performance and memory profiling/benchmarking required to support high performance and efficient AI SW stack on SoCs supporting Edge-AI use cases using Qualcomm’s AI SW SDK and associated components/toolchains
  • Validate, analyze, and optimize the performance and accuracy of software through detailed testing of machine learning use cases.
  • Debug complex issues, perform root cause analysis, and ensure high system reliability.
  • Collaborate with cross-functional teams to deliver robust, scalable toolchains
  • Contribute to a culture of technical excellence, knowledge sharing, and continuous improvement within the AI Software team.
  • Participate in design and code reviews.
  • Work independently with minimal supervision.
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