Senior AI Researcher, -Device LLM Efficiency

About the Role

As a leading technology innovator, Qualcomm pushes the boundaries of what's possible to enable next-generation experiences and drives digital transformation to help create a smarter, connected future for all. As a Qualcomm Machine Learning Researcher, you will conduct fundamental research that creates innovative machine learning methodology that achieves beyond state-of-the-art performance. Qualcomm Engineers collaborate with cross-functional teams to enhance the world of mobile, edge, auto, and IOT products through machine learning research.

• Research and development in the area of LLM inference efficiency algorithms, efficient model architecture design, and/or LLM training
• Develop creative solutions with consideration of practical challenges on devices
• Implementation and evaluation of possible solutions in both simulation and on-device environments

• Master's degree in Computer Engineering, Computer Science, Electrical Engineering, or related field and 2+ years of Hardware Engineering, Software Engineering, Systems Engineering, or related work experience. OR PhD in Computer Engineering, Computer Science, Electrical Engineering, or related field.
• 6+ months of academic and/or work experience developing and/or optimizing machine learning models, systems, platforms, or methods.

• Master's degree in Computer Science, Electrical Engineering, or related field
• 4+ years of AI research experience
• Strong background in deep learning and Transformers
• Strong programming skills in Python and Py Torch
• Experience in LLM reasoning or inference acceleration research

• PhD in Computer Science, Electrical Engineering, or related field
• Experience in LLM efficiency research such as efficient attention, inference acceleration, or KV cache compression
• Experience in on-device AI deployment on mobile or edge devices
• Publishing research papers at top-tier AI/ML conferences, e.g., NeurIPS, ICML, and ICLR, as a lead author