Company:
Qualcomm Canada ULC
Job Area:
Engineering Group, Engineering Group > Machine Learning Engineering
General Summary:
As a leading technology innovator, Qualcomm pushes the boundaries of what's possible to enable next-generation experiences and drives digital transformation to help create a smarter, connected future for all. As a Qualcomm Machine Learning Engineer, you will create and implement machine learning techniques, frameworks, and tools that enable the efficient discovery and utilization of state-of-the-art machine learning solutions over a broad set of technology verticals or designs. Qualcomm Engineers collaborate with cross-functional teams to enhance the world of mobile, edge, auto, and IOT products through machine learning hardware and software.
Minimum Qualifications:
• Bachelor's degree in Computer Science, Engineering, Information Systems, or related field.
Job Description Summary:
AI’s ability to solve complex problems across multiple domains is transformative. Here in the artificial intelligence software group. We are building highly optimized on-device AI solutions. We combine high performance software with cutting edge hardware to run deep neural nets with that little computer you keep in your pocket, that car you drive, or that vacuum cleaner you unleash to clean your house. Come join us if you want to work on bleeding edge AI technology. In this position you will build high performance software for AI engines which include Snapdragon Neural Processing Engine, Android NN, Tensorflow Lite delegate and many more. We develop new tools and SDKs to extend our AI solutions into industry leading customer use cases.
Responsibilities:
- Development of optimization algorithms for ML operators/layers for the Qualcomm AI SW stack
- Development of AI SW stack framework enhancements for optimal resource usage while running a neural network on Qualcomm hardware
- Development of software tools for profiling, and debugging to support rapid deployment of new neural networks in this fast-changing field
- Evaluating and optimizing neural networks’ runtime performance and accuracy
- Working with customer teams to enable state-of-the-art network models and new AI SW features to meet customer use-cases
- Collaborating with AI hardware and architecture teams to continuously improve our AI solution
- Being an active contributor to the development process to ensure commercial quality software releases
- University grads welcome!
Ideal candidates will demonstrate the following:
- Enjoy software development with excellent programming capability and analytical, development, and debugging skills
- Curiosity and willingness to continually learn new things and propose new ideas
- Experience with C/C++, Python
- C++ work experience
- Android or embedded Linux software development preferred
- Optimizing algorithms for hardware acceleration cores using OpenCL, OpenGL ES, and / or DSPs
- Experience with Python numpy and deep learning frameworks such as TensorFlow, PyTorch
- Background in mathematical operations: linear algebra, fast math libraries, multi-threading and vector instruction sets
- Excellent communication skills (verbal, presentation, written)
- Ability to collaborate across a globally diverse team and multiple interests
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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If you would like more information about this role, please contact Qualcomm Careers.