Bachelor's degree in Electrical Engineering, Computer Engineering, Computer Science, or a related field, or equivalent practical experience.
10 years of experience with industry-standard tools, languages and methodologies relevant to the development of silicon-based integrated circuits (ICs) and chips.
7 years of experience in hardware engineering, with a focus on chip design and architecture for machine learning applications.
Experience in the design and optimization of specialized machine learning accelerators (e.g., GPUs).
Experience designing modern computer architecture, including CPUs, GPUs, and memory systems.
Experience in analog computing or energy efficient ASIC design.
Preferred qualifications:
Master's degree or PhD in Electrical Engineering, Computer Engineering or Computer Science, with an emphasis on computer architecture.
Experience in performance analysis and optimization of hardware designs.
Experience collaborating with cross-functional teams, including software engineers and research scientists.
Understanding of large language models (LLMs) and transformer architectures.
Proven track record of leading technical projects and delivering successful hardware solutions.
Familiarity with hardware-software co-design principles and practices.