Responsibilities
Develop software for the Qualcomm AI Stack SDKs, specifically QAIRT and Genie, to support the execution of the latest generative AI models on Snapdragon platforms.
Design and implement core components of Qualcomm AI Stack runtime framework for inference on resource constrained AI systems, operating in low power, small memory footprint platforms
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 AI software solutions.
Assist in feature development and application of machine learning techniques into products and AI solutions, enabling customers to do the same.
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.
Minimum Qualifications (Must Have)
Bachelor’s degree in Engineering, Information Systems, Computer Science, or related field.
Projects or Internships experience (Entry level) / 2+ years (Senior) of general software development experience.
Proficiency in software development using C/C++.
Experience with development in a Linux environment.
Strong software development skills, including data structure and algorithm design, object-oriented or other software design paradigms, software debugging, and testing.
Excellent communication skills (verbal, presentation, and writing).
Preferred Qualifications (Desired)
Master’s degree in Computer Science, Computer Engineering, or Electrical Engineering.
1+ years of experience building embedded software applications.
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 various platforms such as Linux, Android, or Windows.
Knowledge of low-level interactions between operating systems (e.g., Linux, Android, Windows) and hardware.
Experience with CMake-based build environments.
