Overview
Senior Embedded Software Engineer Jobs in Markham, Canada at Qualcomm
Title: Senior Embedded Software Engineer
Company: Qualcomm
Location: Markham, Canada
Category:
Company:
Qualcomm Canada ULC
Job Area:
Engineering Group, Engineering Group Machine Learning Engineering
General
Summary:
As a member of the Low Power AI Solutions team, you will play a critical role in enabling efficient deployment of AI models on Qualcomm’s low-power AI accelerators. This position focuses on developing and optimizing the machine learning runtime framework for inference workloads on embedded edge devices. You will be responsible for implementing performance-critical components of the machine learning runtime framework and applying advanced optimization techniques.
This role includes adding runtime support for popular ML architectures that are best suited for 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. New Headcount.
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, Tensor Flow, PyTorch) onto Qualcomm’s inference stack.
Required
Skills & Experience:
Strong hands-on experience in
performance optimization
for embedded or low-power systems.
Proficient in
C/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 development environments
and tool chains.
Familiarity with
computer architecture , especially for AI accelerators or DSPs.
Basic knowledge of
machine learning concepts
and model structures.
Preferred Qualifications:
Master’s degree in Computer Science, Engineering, or related field.
2+ years of experience with ML frameworks (e.g., Tensor Flow, PyTorch, ONNX).
2+ years of experience in embedded system development and optimization for ML inference.
2+ years of experience with C/C++ in performance-critical environments.
Experience with low-level OS interactions (Linux, Android, QNX).
Familiarity with quantization, graph optimization, and model deployment pipelines.
Experience working in cross-functional teams and large matrixed organizations.
Minimum Qualifications:
•
Bachelor’s degree in Computer Science, Engineering, Information Systems, or related field and 2+ 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 1+ year of Hardware Engineering, Software Engineering, Systems Engineering, or related work experience.
OR
PhD in Computer Science, Engineering, Information Systems, or related field.
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
disabili
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).
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.
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