Qualcomm Technologies, Inc. is looking to develop, implement, and optimize cutting-edge machine learning techniques, frameworks, and tools to enable the efficient utilization of state-of-the-art solutions across a broad set of technology verticals and designs.
Requirements
- 2+ years of experience with Machine Learning frameworks (e.g., Tensor Flow, Caffe, Caffe 2, Pytorch, Keras).
- 2+ years of experience in embedded system development and optimization with application to a specific problem domain in ML (e.g., NLP, multi-media).
- 2+ years of experience with one or more programming language suitable for machine learning (e.g., Python, R, C, C++).
- 2+ years of experience using statistics and probability (e.g., conditional probability, Bayes rule).
- 1+ year of experience with low level interactions between operating systems (e.g., Linux, Android, QNX) and Hardware.
- Experience with ONNX Runtime, Executorch and TFLite/LiteRT frameworks.
- Experience with machine learning techniques, frameworks, and tools
Responsibilities
- Design, develop, and optimize features for the Qualcomm AI Stack SDKs and tools to support execution of the latest neural networks on Snapdragon platforms.
- Design, develop, and optimize features for ONNX Runtime Execution Provider, ExecuTorch Edge IR graph lowering stack, and LiteRT delegates.
- Validate, analyze, and optimize the performance and accuracy of software through detailed testing of machine learning use cases.
- Assist in debugging complex issues, perform root cause analysis, and ensure high system reliability.
- Collaborate with cross-functional teams to deliver robust, scalable AI software solutions.
- Assist in feature development and application of machine learning techniques into products and AI solutions, enabling customers to do the same.
- Contribute to a culture of technical excellence, knowledge sharing, and continuous improvement within the AI Software team.
Other
- 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.
- 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.
- PhD in Computer Science, Engineering, Information Systems, or related field.
- Works independently with minimal supervision.
- Decision-making may affect work beyond immediate work group.
