Intel
PRC, Shanghai
Conducts design and development to build and optimize AI software. Designs, develops, and optimizes for AI frameworks (e.g., SGLang) and contribute to public upstream. Implements various distributed algorithms such as model/data parallel frameworks, parameter servers, dataflow based asynchronous data communication in machine learning, and/or deep learning frameworks. Transforms computational graph representation of neural network model, and develops machine learning and/or deep learning primitives in mathematical libraries. Profiles distributed deep learning models to identify performance bottlenecks and proposes solutions across individual component teams. Optimizes code for various computing hardware backends, and interacts with machine learning and/or deep learning researchers, and utilizing experience with machine learning and/or deep learning frameworks.
Qualifications
• Master degree or Ph.D. in in Computer Science, Artificial Intelligence, Software Engineering, or related fields.
• Good programming skills of modern C++ and Python
• Know foundations of Deep Learning theory and some hands-on experience
• Communicate in English fluently (both written and spoken)
• Are passionate on solving problems and positive thinker
• Experience of performance optimization or high efficiency kernel development experience is a plus
• Experience of PyTorch, SGLang, vLLM is a plus
• Experience of LLM and deep understanding of model structure is a plus
College Grad
Shift 1 (China)
PRC, Shanghai
All qualified applicants will receive consideration for employment without regard to race, color, religion, religious creed, sex, national origin, ancestry, age, physical or mental disability, medical condition, genetic information, military and veteran status, marital status, pregnancy, gender, gender expression, gender identity, sexual orientation, or any other characteristic protected by local law, regulation, or ordinance.
N/A
This role will require an on-site presence. * Job posting details (such as work model, location or time type) are subject to change.
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