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Qualcomm Canada ULC
Job Area
Engineering Group, Engineering Group > Machine Learning Engineering
General Summary
Qualcomm is a company of inventors that unlocked 5G ushering in an age of rapid acceleration in connectivity and new possibilities that will transform industries, create jobs, and enrich lives. But this is just the beginning. It takes inventive minds with diverse skills, backgrounds, and cultures to transform 5Gs potential into world-changing technologies and products. This is the Invention Age - and this is where you come in.
Today, more intelligence is moving to end devices, and mobile is becoming the pervasive AI platform. Building on the smartphone foundation and the scale of mobile, Qualcomm envisions making AI ubiquitous - expanding beyond mobile and powering other end devices, machines, vehicles, and things. We are inventing, developing, and commercializing power-efficient on-device AI, edge cloud AI, and 5G to make this a reality.
The AI Processor System software team is looking for talented and passionate engineers to develop and deliver novel embedded AI solutions to enable state-of-the-art AI models on auto platforms for millions of end users.
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.
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.
Key Responsibilities
- Design and implement core components of the ML runtime framework for inference on embedded systems.
- Collaborate with compiler, hardware, and model teams to co-design efficient execution paths for AI workloads.
- Develop and maintain C/C++ code for runtime kernels and system-level integration.
- Develop tools to assist with performance profiling and debugging of quantized model accuracy
- Analyze and improve runtime behavior using profiling tools and hardware counters.
- Support deployment of models from popular ML frameworks (e.g., Onnx, TensorFlow, PyTorch) onto Qualcomm’s inference stack.
- Challenging the status quo and driving innovations to be the best-of-class.
- Strong hands-on experience in performance optimization for embedded or low-power systems.
- Excellent in C/C++ programming (Rust would be nice to have), with a focus on system-level and runtime development.
- Solid understanding of embedded system design, including memory hierarchy and hardware-software interaction.
- Experience with Linux/Android/QNX development environments and toolchains.
- Familiarity with computer architecture, especially for AI accelerators or DSPs.
- Solid knowledge of machine learning concepts and model structures.
- Optimization of algebraic operations in algorithms for HW cores.
- Knowledge on deep learning and popular frameworks is an asset.
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.
To all Staffing and Recruiting Agencies: Our Careers Site is only for individuals seeking a job at Qualcomm. Staffing and recruiting agencies and individuals being represented by an agency are not authorized to use this site or to submit profiles, applications or resumes, and any such submissions will be considered unsolicited. Qualcomm does not accept unsolicited resumes or applications from agencies. Please do not forward resumes to our jobs alias, Qualcomm employees or any other company location. Qualcomm is not responsible for any fees related to unsolicited resumes/applications.
If you would like more information about this role, please contact Qualcomm Careers.
Key Skills
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