Qualcomm Technologies, Inc. is looking to solve the problem of achieving beyond state-of-the-art performance in machine learning methodology
Requirements
- Strong background in deep learning and Transformers
- Strong programming skills in Python and PyTorch
- Experience in LLM reasoning or inference acceleration research
- 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
Responsibilities
- 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
Other
- Master's degree in Computer Science, Electrical Engineering, or related field
- 4+ years of AI research experience
- PhD in Computer Science, Electrical Engineering, or related field (preferred)
- 2+ years of Hardware Engineering, Software Engineering, Systems Engineering, or related work experience (for PhD holders)
- Qualcomm is an equal opportunity employer; all qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, Veteran status, or any other protected classification
