Company:Qualcomm Canada ULC
Job Area:Engineering Group, Engineering Group > Machine Learning Engineering
General Summary:We are seeking a Machine Learning software engineer with embedded experience.Qualcomm Automotive AI Software team is rapidly expanding to offer optimized solutions for infotainment and ADAS/Autonomous Driving. To scale and strengthen our offering in this domain, we are looking for a talented engineer to develop and deliver novel embedded AI solutions to enable state-of-the-art AI models on auto platforms for millions of end users.
New Headcount.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.
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++ 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.
Required Skills & Experience:- Strong hands-on experience in performance optimization for embedded or low-power systems.
- Excellent in C++ programming, 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.
If you would like more information about this role, please contact Qualcomm Careers.