Silicon Engineer, Power Analysis, DeepMind
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Minimum qualifications:
- 7 years of experience working in ASIC power analysis & optimization, including experience with production chips
- Experience in tape-outs of chips
- Experience interacting and collaborating with silicon foundries and other external vendors for the tapeout process
- Experience with Verilog and industry-standard EDA tools for power analysis & optimization design (e.g., PP-RTLA, PowerArtist, PrimeTime-PX, PrimeTime, Cadence Innovus, Synopsys Fusion Compiler)
- Experience with scripting languages (e.g., Perl, Tcl) for automation of power analysis & optimization flows
- Software development experience
Preferred qualifications:
- Master's degree or PhD in Electrical Engineering, Physics or related field
About the job
Artificial intelligence will be one of humanity’s most transformative inventions. At Google DeepMind, we are a pioneering AI lab with exceptional interdisciplinary teams focused on advancing AI development to solve complex global challenges and accelerate high-quality product innovation for billions of users. We use our technologies for widespread public benefit and scientific discovery, ensuring safety and ethics are always our highest priority.
US: $217000 - $236000 (USD) + 15% bonus target
Learn more about benefits at Google.
Responsibilities
- Architect advanced technology node power solutions and establish use case budgets with block and full-chip estimations.
- Lead and drive the automation and integration of power analysis processes—including RTL power analysis, optimization, IP selection, physical design, and timing closure—into our automated flow.
- Apply hardware expertise to build, create, and integrate software components for automated early- and late-stage power analysis and optimization.
- Partner with systems power and cross-functional teams to define, execute, and advocate for power management and reduction methodologies from SoC architecture through sign-off.
- Specify requirements for power management IPs while managing their design, integration, and post-silicon validation.
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