Google welcomes people with disabilities. Minimum qualifications: + Bachelors degree in Electrical Engineering, Computer Engineering, Computer Science, a related field, or equivalent practical experience. + 3 years of experience with computer architecture concepts, with microarchitecture, cache hierarchy, pipelining, and memory subsystems. Preferred qualifications: + Master's degree or PhD in Electrical Engineering, Computer Engineering or Computer Science, with computer architecture. + Experience with Machine Learning Accelerators (e.g., Machine Learning Software models or accelerator architectures). + Experience in Machine Learning algorithms (e.g., recommendation systems, Natural Language Processing (NLP), image). + Experience in architecting and optimizing compilers. + Knowledge of compiler flows (e.g., TensorFlow). Be part of a diverse team that pushes boundaries, developing custom silicon solutions that power the future of Google's direct-to-consumer products. You'll contribute to the innovation behind products loved by millions worldwide. Your expertise will shape the next generation of hardware experiences, delivering 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 the best of Google AI, Software, and Hardware to create radically helpful experiences. We research, design, and develop new technologies and hardware to make computing faster, seamless, and more powerful. We aim to make people's lives better through technology. + Build up tools, flows, and dashboards for Tensor Processing Unit (TPU) power/performance analysis. + Analyze important Machine Learning workloads, evaluate power and performance and propose architecture or compiler improvements. + Analyze micro-architecture of the TPU, engage with the implementation team and propose power or performance optimization opportunities. + Collaborate with cross-functional teams to improve the end to end workload analysis flows, including debugging and tracing. Google is proud to be an equal opportunity workplace and is an affirmative action employer. We are committed to equal employment opportunity regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability, gender identity or Veteran status. We also consider qualified applicants regardless of criminal histories, consistent with legal requirements. See also https://careers.google.com/eeo/ and https://careers.google.com/jobs/dist/legal/OFCCP_EEO_Post.pdf If you have a need that requires accommodation, please let us know by completing our Accommodations for Applicants form: https://goo.gl/forms/aBt6Pu71i1kzpLHe2.