Silicon Engineer, Power Analysis, DeepMind

DeepMind Technologies Limited; Mountain View (CA); On-site; USD 217,000 - 236,000; Full time

Job summary

DeepMind Technologies Limited in Mountain View, CA is seeking an experienced ASIC power engineer to architect advanced power solutions for next-generation chips and tapeouts. You will collaborate with silicon foundries, use Verilog and industry-standard EDA tools, and drive automation for RTL power analysis and optimization across the design flow.

Join a team delivering high-performance, energy-efficient hardware for leading-edge AI products, with compensation reflecting the US market and a 15%

Qualifications

• 7 years of experience in ASIC power analysis & optimization, including production chips.
• Experience in tape-outs of chips.
• Experience interacting and collaborating with silicon foundries and external vendors for tapeouts.
• Experience with Verilog and industry-standard EDA tools for power analysis & optimization (PP-RTLA, PowerArtist, PrimeTime-PX, PrimeTime, Cadence Innovus, Synopsys Fusion Compiler).
• Experience with scripting languages (Perl, Tcl) for automation of power analysis & optimization flows.
• Software development experience.

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—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.

Skills

ASIC power analysis

Tape-out experience

Foundry collaboration

Verilog

Perl

Tcl

Software development

Education

Master's degree or PhD in Electrical Engineering, Physics or related field

Tools

PP-RTLA

PowerArtist

PrimeTime-PX

PrimeTime

Cadence Innovus

Synopsys Fusion Compiler

Job description

• 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

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

Be part of a 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.

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.

We are pushing the boundaries across multiple domains. Our global teams offer diverse learning opportunities and varied career pathways for those driven to achieve exceptional results through collective effort.

Individual pay is determined by factors including job-related skills, experience, and relevant education or training.

US: $217000 - $236000 (USD) + 15% bonus target

Responsibilities

Learn more about benefits at Google .

• 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.

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 Google's EEO Policy and EEO is the Law. If you have a disability or special need that requires accommodation, please let us know by completing our Accommodations for Applicants form .