As a Machine Learning Engineer at Qualcomm, you will be at the forefront of technology innovation, creating and implementing machine learning techniques and frameworks. You will work collaboratively with cross-functional teams to enhance mobile, edge, auto, and IoT products through advanced machine learning solutions. This role requires a strong understanding of machine learning compiler concepts and hands-on experience with various compiler stacks. You will also be responsible for building debugging tools and mentoring teammates while contributing to the development of efficient code for device chips.

• Bachelor's degree in Computer Science, Engineering, Information Systems, or related field and 2+ years of relevant work experience, or a Master's degree with 1+ year of experience, or a PhD in a related field.
• 3+ years of industry experience in ML infrastructure, compiler engineering, or AI framework development.
• Proficient in Python and C++.
• Solid understanding of ML compiler concepts and hands-on experience with compiler stacks such as MLIR, ONNX, or TVM.
• Experience with PyTorch model export and on-device deployment frameworks.

• Build and maintain machine learning compiler technologies that convert AI models into efficient code for device chips.
• Contribute to AI hub compiler and ONNX Runtime QNN by performing graph optimization and partitioning.
• Develop debugging tools to identify and resolve failures, accuracy loss, or performance slowdowns.
• Mentor teammates and provide technical guidance while solving open-ended problems independently.
• Communicate complex compiler ideas clearly to chip engineers, business partners, and external developers.

• Qualcomm offers competitive compensation, annual bonuses, stock programs, comprehensive healthcare coverage, retirement plans, wellness programs, parental leave, flexible work options, and professional development opportunities.