Machine Learning Engineer

Qualcomm Technologies, Inc. is a technology innovator developing solutions for mobile, edge, automotive, and IoT products. The Machine Learning Engineer will create and implement machine learning techniques, frameworks, and tools, while assisting with hardware and software optimization, algorithm development, and AI solution deployment.

What you'll do:

• Applies Machine Learning knowledge to assist in extending training or runtime frameworks or model efficiency software tools with new features and optimizations
• Assists in the modeling, architecture, and development of machine learning hardware (co-designed with machine learning software) for inference or training solutions
• Assists in the development of optimized software to enable AI models deployed on hardware (e.g., machine learning kernels, compiler tools, or model efficiency tools, etc.) to allow specific hardware features; collaborates with team members for joint design and development
• Assists with the development and application of machine learning techniques into products and/or AI solutions to enable customers to do the same
• Develops, adapts, or prototypes machine learning algorithms, models, or frameworks in alignment with product roadmap

What they're looking for:

• Bachelor's degree in Computer Science, Engineering, Information Systems, or related field
• Master's degree in Computer Science, Engineering, Information Systems, or related field
• 1+ year of experience with Machine Learning frameworks (e.g., Tensor Flow, Caffe, Caffe 2, Pytorch, Keras)
• 1+ year of experience in embedded system development and optimization with application to a specific problem domain in ML (e.g., NLP, multi-media)
• 1+ year of experience with one or more programming language suitable for machine learning (e.g., Python, R, C, C++)
• 1+ year of experience using statistics and probability (e.g., conditional probability, Bayes rule)
• 1+ year of experience working in a large matrixed organization
• 6+ months of experience with low level interactions between operating systems (e.g., Linux, Android, QNX) and Hardware

Benefits:

• Competitive annual discretionary bonus program
• Opportunity for annual RSU grants