Requirements

• PhD in Computer Science, Electrical Engineering, or a related field and at least 10 years of industry or research experience in the field
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• Solid background in Machine Learning systems research and experience with performance evaluation and performance modeling
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• Hands-on experience with machine learning / deep learning methods and extensive knowledge of Large Language Model training and inference frameworks
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• Academic publications in relevant journals and industry conferences
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• Strong knowledge of AI systems, including compute (GPUs, TPUs, etc.) and networking (Ethernet, Infiniband, NVLink, etc.) technologies, and their various topologies, paradigms, and trade-offs
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• Proven track record leading a team to deliver published results
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• (Desirable) Demonstrated ability to creatively problem-solve and apply first-principles thinking to generate novel ideas, particularly in ambiguous, evolving environments
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