About The Position

Qualcomm AI Research is looking for talented AI software engineers to enable AI technologies on edge devices. This is your opportunity to join a high-caliber team of engineers, building best-in-class GenAI solutions with model optimization tools to deploy state-of-the-art models to edge devices with optimal power, memory, and computation use. In this role, you will be part of a multi-disciplinary team that has continually enabled first-of-its-kind and competitive generative AI models on Qualcomm AI accelerator engines, such as the world’s first on device text-to-image generation with stable diffusion, and text-to-text with 7B large language model on device. You will collaborate in a cross-functional environment spanning hardware, software and systems and see your design in action on industry-leading chips embedded in the next generation of intelligent devices, such as smartphones, autonomous vehicles, robotics, and IOT devices.

Requirements

  • Bachelor's degree in Computer Science, Engineering, Information Systems, or related field and 2+ years of Hardware Engineering, Software Engineering, Systems Engineering, or related work experience.
  • OR Master's degree in Computer Science, Engineering, Information Systems, or related field and 1+ year of Hardware Engineering, Software Engineering, Systems Engineering, or related work experience.
  • OR PhD in Computer Science, Engineering, Information Systems, or related field.

Nice To Haves

  • At least 3 years of work experience in a relevant field.
  • Excellent programming capabilities with C/C++ and Python.
  • Knowledge of deep learning and ML frameworks ( i.e. PyTorch ).
  • Strong software design, development, and debugging skills.
  • Knowledge of Android programming is plus.
  • Familiarity of embedded platforms and programming.
  • Experience with the Qualcomm AI Software Stack + SDKs is a plus

Responsibilities

  • Development of end-to-end embedded AI software to orchestrate neural network models on Qualcomm leading edge hardware as part of Qualcomm’s AI Research team.
  • Implementation, debugging and profiling of agentic software solutions.
  • Design and enhance the implementation of ML/AI SW stack and runtime software to improve performance and power efficiency.
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