SW Engineer, Constrained AI Software

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 a Qualcomm AI 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 the AI Software team, we build the Qualcomm AI Engine to enable OEMs and developers to run their Machine Learning workloads on Qualcomm's low-power AI accelerators in a Constrained Operating Environment.

In this position, you will be responsible for assisting with the software design and development of the Qualcomm AI engine that enables OEMs and developers to run their Machine Learning workloads on Qualcomm's low-power AI accelerators. Your work will directly impact the runtime efficiency, latency, and power consumption of AI applications running on Qualcomm hardware deployed on cars, notebook computers, phones, and wearables. Come join us to work on bleeding edge AI technology.

Responsibilities:

• Design and implement core components of the ML runtime framework for inference on Constrained AI systems, operating in low power, small memory footprint platforms
• Develop and maintain C/C++ code for runtime kernels and system-level integration
• Development of model analyzing tools for internal and external customers
• Development and profiling of performance KPIs and footprint across AI workloads for platforms such as Android/Aluminum, Linux, QNX, Windows and future platforms
• Track and adopt leading 3rd party AI toolchains across Qualcomm AI platforms/SoCs
• Address issues found in existing and past Qualcomm AI products
• Debug customer machine learning use cases executing on Qualcomm AI Stack
• Communication across globally diverse team
• Participate in software quality process improvements

• Bachelor's degree in Computer Science, Engineering, Information Systems, or related field., * Master's degree in Computer Science, Computer Engineering, or Electrical Engineering
• 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 Hexagon DSP SDK or cross compiler toolchains for embedded systems
• Familiarity with TensorFlow, PyTorch or ONNX
• Experience using/integrating Qualcomm AI Stack products (e.g. QAIRT, QNN, Genie).
• 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.
• Experience with agile software development practices and git-based SCM.
• Ability to collaborate across a globally diverse team and manage multiple interests.

4.04.0 out of 5 stars San Diego, CA $122,800 - $184,200 a year, Qualcomm expects its employees to abide by all applicable policies and procedures, including but not limited to security and other requirements regarding protection of Company confidential information and other confidential and/or proprietary information, to the extent those requirements are permissible under applicable law.

Pay range and Other Compensation & Benefits : $122,800.00 - $184,200.00

The above pay scale reflects the broad, minimum to maximum, pay scale for this job code for the location for which it has been posted. Even more importantly, please note that salary is only one component of total compensation at Qualcomm. We also offer a competitive annual discretionary bonus program and opportunity for annual RSU grants (employees on sales-incentive plans are not eligible for our annual bonus). In addition, our highly competitive benefits package is designed to support your success at work, at home, and at play. Your recruiter will be happy to discuss all that Qualcomm has to offer - and you can review more details about our US benefits at this link .