Staff Embedded Machine Learning Engineer

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. Replacement. 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. Applicants: Qualcomm is an equal opportunity employer. If you are an individual with a disability and need an accommodation during the application/hiring process, rest assured that Qualcomm is committed to providing an accessible process. You may e-mail disability-accomodations@qualcomm.com or call Qualcomm's toll-free number found here. Upon request, Qualcomm will provide reasonable accommodations to support individuals with disabilities to be able participate in the hiring process. Qualcomm is also committed to making our workplace accessible for individuals with disabilities. (Keep in mind that this email address is used to provide reasonable accommodations for individuals with disabilities. We will not respond here to requests for updates on applications or resume inquiries). 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Pay range and Other Compensation & Benefits: $131,200.00 - $181,200.00 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. If you would like more information about this role, please contact Qualcomm Careers.