Accelerator Architect and Performance Engineer, Generative AI Apply info_outline info_outline X Info Note: By applying to this position you will have an opportunity to share your preferred working location from the following: Mountain View, CA, USA; San Diego, CA, USA . Minimum qualifications: Bachelor's degree in Electrical Engineering, Computer Engineering, Computer Science, or a related field, or equivalent practical experience. 8 years of work or academic research experience in computer or chip architecture, performance, or compiler. Experience with Generative AI model architectures (e.g., Large Language Models, Vision Transformers, Image Diffusion Models, etc.). Experience with one or more general purpose programming languages including (but not limited to) C/C++ or Python and deep learning frameworks like TensorFlow, Jax, or Pytorch. Preferred qualifications: Master's degree or PhD in Electrical Engineering, Computer Engineering, or Computer Science, with an emphasis on computer architecture. Experience with domain-specific accelerators. Experience with distributed/parallel programming. Experience with hardware/software co-design for machine learning. Experience with simulator development and micro-architecture. About the job Join a team that pushes boundaries in developing custom silicon solutions powering Google's future products. Contribute to innovations behind products loved by millions, shaping next-generation hardware experiences for unparalleled performance, efficiency, and integration. Google's mission is to organize the world's information and make it universally accessible and useful. Our team combines Google AI, Software, and Hardware to create radically helpful experiences, researching, designing, and developing new technologies to make computing faster, seamless, and more powerful. Our goal is to improve people's lives through technology. Responsibilities Drive forward-looking Generative AI machine learning architecture exploration for Tensor mobile SoCs, collaborating across research, system architecture, and compiler teams to optimize workloads across the tech stack. Work with researchers and program management to define system architecture requirements for future Generative AI use cases. Apply advanced research in architecture and process technology to achieve breakthrough power and performance improvements on Generative AI workloads. Optimize performance of Generative AI use cases by defining optimal model scheduling on TPU compute engines. Google is proud to be an equal opportunity and affirmative action employer. We are committed to building a diverse workforce and providing equal employment opportunities regardless of race, creed, color, religion, gender, sexual orientation, gender identity/expression, national origin, disability, age, genetic information, veteran status, marital status, pregnancy or related conditions, or any other legally protected status. See Google's EEO Policy and related resources for more information. As a global company, English proficiency is required for all roles to facilitate collaboration and communication worldwide. Note to recruitment agencies: Google does not accept agency resumes. Please do not forward resumes to our jobs alias, Google employees, or any other organization. We are not responsible for fees related to unsolicited resumes. #J-18808-Ljbffr Google
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