Senior AI Researcher, On-Device LLM Efficiency
Qualcomm•San Diego, CA
2d
About The Position
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.
Requirements
- 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 PyTorch
- Experience in LLM reasoning or inference acceleration research
Nice To Haves
- 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
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
Benefits
- competitive annual discretionary bonus program
- opportunity for annual RSU grants
- highly competitive benefits package
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What This Job Offers
Job Type
Full-time
Career Level
Senior
Number of Employees
5,001-10,000 employees
