Deep expertise in neural network architectures, model compression (e.g., quantization, pruning, knowledge distillation) and efficient inference algorithm
Strong background on compiler stack and ML system optimization for AI accelerators (e.g., graph transformation, graph tiling and scheduling, tensor layout/memory optimization)
Strong understanding of Machine Learning fundamentals, strong programming skills with ML frameworks
Hands-on experience with model development pipelines for AI accelerator, including training, fine-tuning, evaluation, and performance optimization.
Preferred Qualifications
PhD in Computer Science, Electrical Engineering, or related fields or MS with AI research, or related work experience.
Extensive experience in deep learning research and impactful publications in top-tier machine learning venues (NeurIPS, ICML, ICLR, CVPR, ICCV, ACL, EMNLP etc.).
Experience in on-device model deployment and optimization algorithms for AI hardware accelerators
Experience working with a variety of stakeholders and ability to communicate complex outcomes to a wide range of audiences.
Minimum Qualifications
- 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.
- OR
- 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.
- OR
- PhD in Computer Science, Engineering, Information Systems, or related field.
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Pay range and Other Compensation & Benefits
$114,400.00 - $164,400.00
The above pay scale reflects the broad, minimum to maximum, pay scale for this job code for the location for which it has been posted. Even more importantly, please note that salary is only one component of total compensation at Qualcomm. We also offer a competitive annual discretionary bonus program and opportunity for annual RSU grants (employees on sales-incentive plans are not eligible for our annual bonus). In addition, our highly competitive benefits package is designed to support your success at work, at home, and at play. Your recruiter will be happy to discuss all that Qualcomm has to offer.
If you would like more information about this role, please contact Qualcomm Careers.
