design technology co-optimization engineer

about the job
in this role, youll work to shape the future of ai/ml hardware acceleration. you will have an opportunity to drive cutting-edge tpu (tensor processing unit) technology that powers google's most demanding ai/ml applications. youll be part of a team that pushes boundaries, developing custom silicon solutions that power the future of google's tpu. you'll contribute to the innovation behind products loved by millions worldwide, and leverage your design and verification expertise to verify complex digital designs, with a specific focus on tpu architecture and its integration within ai/ml-driven systems.
as a design technology co-optimization (dtco) engineer, you will bridge the gap between process technology and product architecture to define the next generation of datacenter-class silicon. you will be responsible for extracting maximum process entitlement by evaluating advanced logic nodes and emerging transistor architectures.in this role, you will conduct place and route e

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minimum qualifications:
bachelor's degree in electrical engineering, computer engineering,  Computer Science, or a related field, or equivalent practical experience.
2 years of experience in physical design (rtl-to-gds) or technology development, focusing on advanced nodes (e.g., 7nm, 5nm, or below).
experience with industry-standard place and route (p&r) tools and static timing analysis (sta) tools.
experience in cmos device physics, finfet/nanosheet architectures, and the impact of layout parasitics on ppa.
experience in scripting and automation using tcl and  Python (or  PERL ) to manage design sweeps and  data extraction.
preferred qualifications:
master's degree or phd in electrical engineering, computer engineering or  Computer Science, with an emphasis on computer architecture.
experience in design technology co-optimization (dtco), including standard cell library characterization, metal stack optimization, and evaluation of scaling boosters (e.g., backside power deliver