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Qualcomm Staff Engineer- GPU Machine Learning SW Architect 
Canada, Ontario, Markham 
585584086

07.09.2024

Job Area:

Engineering Group, Engineering Group > Machine Learning Engineering

In this role, you will work in a dynamic research environment, be part of a multi-disciplinary team of researchers and software developers, work with popular neural network frameworks, and understand the architecture of Qualcomm’s SOC compute and ML HW accelerators. You will architect, design, develop & test on-device software to enable on-device training on edge devices, develop Machine learning Kernels using OpenCL and optimizatizing them for efficient execution for Adreno GPU.

The successful applicant should have a strong embedded and machine learning framework software architecture and design background, and passion to work on on-device software. Prior working experience developing software for GPU is required.

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.

PhD in Computer Science, Engineering, Information Systems, or related field and 2+ years of Hardware Engineering, Software Engineering, Systems Engineering, or related work experience.

Ideal candidates will demonstrate one or more of the following:

  • 5+ years of GPU programming for GPUs/Frameworks such as CUDA, OpenCL, Qualcomm Adreno, Nvidia GPU, AMD GPU, Mali GPU and Machine learning Kernel development and optimization experience.

  • 5+ years of working experience developing on-device software.

  • Knowledge of neural networks, with hands-on experience using ML frameworks such as TensorFlow or PyTorch

  • Experience deploying ML models on edge devices.

  • Debugging and analysis skills, for root-causing complex issues

  • Experience profiling on-device software to find runtime and memory bottlenecks and optimizing the same.

  • Experience with source code and configuration management tools, such as Git

  • Previous experience working in an Agile environment and collaborating with multi-disciplinary teams.

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.