Qualcomm - San Diego, CA

posted about 1 month ago

Full-time - Mid Level
San Diego, CA
1,001-5,000 employees
Computer and Electronic Product Manufacturing

About the position

The Senior QCT Applications Engineer - Machine Learning SW at Qualcomm is responsible for developing and deploying machine learning applications optimized for Qualcomm's AI hardware accelerators. This role involves working closely with partners to create best-in-class ML applications using frameworks like PyTorch, TensorFlow, ONNX, and Caffe2, while ensuring high performance in terms of throughput, latency, and accuracy. The engineer will also be involved in model profiling, optimization, and providing customer documentation and training.

Responsibilities

  • Develop and deploy machine learning applications based on frameworks such as PyTorch, TensorFlow, ONNX, and Caffe2.
  • Assess models for throughput, latency, and accuracy.
  • Profile and optimize machine learning models.
  • Develop end-to-end application pipelines and integrate with customer frameworks.
  • Provide customer documentation, training, and demos.

Requirements

  • Bachelor's degree in Engineering, Information Systems, Computer Science, or related field and 2+ years of Software Applications Engineering or related work experience, OR a Master's degree with 1+ year of experience, OR a PhD in a related field.
  • 1+ year of experience with programming languages such as C, C++, Java, Python.
  • 1+ year of experience with debugging techniques.

Nice-to-haves

  • Hands-on experience with deep learning models on ML frameworks like PyTorch and TensorFlow.
  • Experience profiling and optimizing software.
  • Experience with C++ and Python.
  • Experience developing software solutions in Linux environments, including containers and virtual machines.
  • Knowledge of source code and configuration management tools, particularly git.

Benefits

  • Competitive annual discretionary bonus program
  • Opportunity for annual RSU grants
  • Comprehensive benefits package designed to support work-life balance
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