Lead new features development for Qualcomm AI Runtime SDK and collaborate with global cross functional team as part of the software development lifecycle
Lead project discussions and analysis on system and model deployment designs for GenAI models
Use cross compiler toolchains for embedded systems such as Android, embedded Linux, Windows on Snapdragon and QNX
Implement and optimize Machine Learning operations using modern C++17 on Hexagon DSP systems
Contribute to the development of tools and GenAI workflows for chip design, model and system analysis
Participate in software quality process improvements
Preferred Qualifications
Six or more years of relevant work experience
Experience with modern C++17 language features and C++ design patterns
Background in mathematical algorithms using fast math libraries and vector instructions sets
Practical experience with developing middleware or firmware software
Experience with multitasking and multithreading driver development
Experience with Hexagon DSP SDK or cross compiler toolchains for embedded systems and JIT technologies
Experience with low level interactions between operating systems and hardware.
Experience with Qualcomm FastRPC and Windows MCDM drivers
Experience using/integrating Qualcomm AI Stack products (e.g. QNN, SNPE, QAIRT)
Familiarity with TensorFlow, PyTorch or ONNX
Experience with agile software development practices, Jira system and tools such as git
Ability to collaborate and lead discussions across a globally diverse team
Education Requirements
Minimum: Bachelor's degree in Computer Science, Computer Engineering, or Electrical Engineering
Preferred: Master's degree in Computer Science, Computer Engineering, or Electrical Engineering
Minimum Qualifications
- Bachelor's degree in Computer Science, Engineering, Information Systems, or related field and 4+ 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 3+ years of Hardware Engineering, Software Engineering, Systems Engineering, or related work experience.
- OR
- PhD in Computer Science, Engineering, Information Systems, or related field and 2+ years of Hardware Engineering, Software Engineering, Systems Engineering, or related work experience.
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